diff --git a/docs/articles/getting-started.html b/docs/articles/getting-started.html index 6a266ca1..1eafea08 100644 --- a/docs/articles/getting-started.html +++ b/docs/articles/getting-started.html @@ -97,18 +97,18 @@

Example tidy_normal() #> # A tibble: 50 × 7 -#> sim_number x y dx dy p q -#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 1 0.497 -3.23 0.000378 0.690 0.497 -#> 2 1 2 -0.660 -3.10 0.000998 0.255 -0.660 -#> 3 1 3 -0.813 -2.97 0.00236 0.208 -0.813 -#> 4 1 4 0.0533 -2.84 0.00498 0.521 0.0533 -#> 5 1 5 0.664 -2.72 0.00944 0.747 0.664 -#> 6 1 6 -0.861 -2.59 0.0161 0.195 -0.861 -#> 7 1 7 0.308 -2.46 0.0246 0.621 0.308 -#> 8 1 8 1.37 -2.33 0.0341 0.914 1.37 -#> 9 1 9 -1.34 -2.20 0.0433 0.0897 -1.34 -#> 10 1 10 0.685 -2.08 0.0512 0.753 0.685 +#> sim_number x y dx dy p q +#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 1 1 -0.883 -3.47 0.000214 0.189 -0.883 +#> 2 1 2 -1.62 -3.31 0.000612 0.0523 -1.62 +#> 3 1 3 -0.181 -3.16 0.00153 0.428 -0.181 +#> 4 1 4 0.549 -3.00 0.00337 0.709 0.549 +#> 5 1 5 -0.109 -2.84 0.00657 0.456 -0.109 +#> 6 1 6 -0.446 -2.69 0.0114 0.328 -0.446 +#> 7 1 7 1.08 -2.53 0.0179 0.859 1.08 +#> 8 1 8 -0.758 -2.37 0.0257 0.224 -0.758 +#> 9 1 9 0.262 -2.21 0.0344 0.603 0.262 +#> 10 1 10 0.516 -2.06 0.0436 0.697 0.516 #> # … with 40 more rows

An example plot of the tidy_normal data.

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diff --git a/docs/news/index.html b/docs/news/index.html
index a8b527e6..e257af47 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -78,6 +78,14 @@ 
Minor Fixes and Improv
 
  • Fix #309 - Add function for internal use to drop dependency of stringr. Function is dist_type_extractor() which is used for several functions in the library.
    • 
 
  • Fix #310 - Update combine-multi-dist to use dist_type_extractor()
 
    • 
+
  • Fix #311 - Update all util_dist_stats_tbl() functions to use dist_type_extractor()
+
    • 
+
  • Fix #316 - Update all autoplot functions for tidy_bernoulli()
+
    • 
+
  • Fix #312 - Update random walk function to use dist_type_extractor()
+
    • 
+
  • Fix #314 - Update tidy_stat_tbl() to use dist_type_extractor()
+
    •
    diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index 4d85895d..90f5ca3e 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -3,7 +3,7 @@ pkgdown: 2.0.6 pkgdown_sha: ~ articles: getting-started: getting-started.html -last_built: 2022-10-11T18:38Z +last_built: 2022-10-11T19:55Z urls: reference: https://www.spsanderson.com/TidyDensity/reference article: https://www.spsanderson.com/TidyDensity/articles diff --git a/docs/reference/Rplot002.png b/docs/reference/Rplot002.png index 966339c7..2d733eda 100644 Binary files a/docs/reference/Rplot002.png and b/docs/reference/Rplot002.png differ diff --git a/docs/reference/bootstrap_density_augment.html b/docs/reference/bootstrap_density_augment.html index cf3403f3..81244004 100644 --- a/docs/reference/bootstrap_density_augment.html +++ b/docs/reference/bootstrap_density_augment.html @@ -114,18 +114,18 @@

    Examplestidy_bootstrap(x) %>% bootstrap_density_augment() #> # A tibble: 50,000 × 5 -#> sim_number x y dx dy -#> <fct> <int> <dbl> <dbl> <dbl> -#> 1 1 1 17.8 4.05 0.0000865 -#> 2 1 2 15.8 5.50 0.000546 -#> 3 1 3 15.8 6.94 0.00228 -#> 4 1 4 13.3 8.39 0.00671 -#> 5 1 5 13.3 9.83 0.0156 -#> 6 1 6 13.3 11.3 0.0314 -#> 7 1 7 27.3 12.7 0.0543 -#> 8 1 8 16.4 14.2 0.0756 -#> 9 1 9 15.2 15.6 0.0839 -#> 10 1 10 18.7 17.1 0.0796 +#> sim_number x y dx dy +#> <fct> <int> <dbl> <dbl> <dbl> +#> 1 1 1 21.4 6.91 0.000155 +#> 2 1 2 17.8 8.18 0.00223 +#> 3 1 3 30.4 9.45 0.00981 +#> 4 1 4 22.8 10.7 0.0134 +#> 5 1 5 10.4 12.0 0.00841 +#> 6 1 6 21.4 13.3 0.0188 +#> 7 1 7 21.4 14.5 0.0410 +#> 8 1 8 15.5 15.8 0.0473 +#> 9 1 9 22.8 17.1 0.0535 +#> 10 1 10 16.4 18.3 0.0682 #> # … with 49,990 more rows tidy_bootstrap(x) %>% @@ -134,16 +134,16 @@

    Examples#> # A tibble: 50,000 × 5 #> sim_number x y dx dy #> <fct> <int> <dbl> <dbl> <dbl> -#> 1 1 1 21 7.53 0.000170 -#> 2 1 2 22.8 8.91 0.00103 -#> 3 1 3 21 10.3 0.00444 -#> 4 1 4 15.8 11.7 0.0139 -#> 5 1 5 18.7 13.1 0.0319 -#> 6 1 6 22.8 14.4 0.0551 -#> 7 1 7 33.9 15.8 0.0738 -#> 8 1 8 14.3 17.2 0.0812 -#> 9 1 9 17.8 18.6 0.0796 -#> 10 1 10 21.4 20.0 0.0745 +#> 1 1 1 24.4 2.49 0.000138 +#> 2 1 2 17.8 3.98 0.000650 +#> 3 1 3 16.4 5.47 0.00227 +#> 4 1 4 14.7 6.96 0.00601 +#> 5 1 5 13.3 8.46 0.0127 +#> 6 1 6 26 9.95 0.0230 +#> 7 1 7 30.4 11.4 0.0382 +#> 8 1 8 15.5 12.9 0.0575 +#> 9 1 9 17.3 14.4 0.0741 +#> 10 1 10 15.2 15.9 0.0785 #> # … with 49,990 more rows

    diff --git a/docs/reference/bootstrap_p_augment.html b/docs/reference/bootstrap_p_augment.html index db6eabf3..67e98b8a 100644 --- a/docs/reference/bootstrap_p_augment.html +++ b/docs/reference/bootstrap_p_augment.html @@ -116,18 +116,18 @@

    Examples bootstrap_unnest_tbl() %>% bootstrap_p_augment(y) #> # A tibble: 50,000 × 3 -#> sim_number y p -#> <fct> <dbl> <dbl> -#> 1 1 30.4 0.936 -#> 2 1 33.9 1 -#> 3 1 19.7 0.561 -#> 4 1 19.2 0.529 -#> 5 1 19.2 0.529 -#> 6 1 19.2 0.529 -#> 7 1 30.4 0.936 -#> 8 1 10.4 0.0607 -#> 9 1 22.8 0.779 -#> 10 1 30.4 0.936 +#> sim_number y p +#> <fct> <dbl> <dbl> +#> 1 1 21.4 0.689 +#> 2 1 21.4 0.689 +#> 3 1 18.7 0.468 +#> 4 1 21.4 0.689 +#> 5 1 30.4 0.939 +#> 6 1 19.2 0.532 +#> 7 1 15.2 0.250 +#> 8 1 15.2 0.250 +#> 9 1 21.5 0.720 +#> 10 1 14.3 0.124 #> # … with 49,990 more rows diff --git a/docs/reference/bootstrap_q_augment.html b/docs/reference/bootstrap_q_augment.html index ca12a050..f1d99ea5 100644 --- a/docs/reference/bootstrap_q_augment.html +++ b/docs/reference/bootstrap_q_augment.html @@ -119,16 +119,16 @@

    Examples#> # A tibble: 50,000 × 3 #> sim_number y q #> <fct> <dbl> <dbl> -#> 1 1 22.8 10.4 -#> 2 1 33.9 10.4 -#> 3 1 18.7 10.4 -#> 4 1 26 10.4 -#> 5 1 30.4 10.4 -#> 6 1 17.3 10.4 -#> 7 1 15.5 10.4 -#> 8 1 30.4 10.4 -#> 9 1 15.8 10.4 -#> 10 1 32.4 10.4 +#> 1 1 17.3 10.4 +#> 2 1 18.7 10.4 +#> 3 1 17.3 10.4 +#> 4 1 17.3 10.4 +#> 5 1 21.4 10.4 +#> 6 1 15 10.4 +#> 7 1 14.7 10.4 +#> 8 1 15 10.4 +#> 9 1 22.8 10.4 +#> 10 1 14.3 10.4 #> # … with 49,990 more rows diff --git a/docs/reference/bootstrap_stat_plot-1.png b/docs/reference/bootstrap_stat_plot-1.png index eacfe95f..338a620a 100644 Binary files a/docs/reference/bootstrap_stat_plot-1.png and b/docs/reference/bootstrap_stat_plot-1.png differ diff --git a/docs/reference/bootstrap_stat_plot-2.png b/docs/reference/bootstrap_stat_plot-2.png index d80078ad..b5e65e27 100644 Binary files a/docs/reference/bootstrap_stat_plot-2.png and b/docs/reference/bootstrap_stat_plot-2.png differ diff --git a/docs/reference/bootstrap_unnest_tbl.html b/docs/reference/bootstrap_unnest_tbl.html index 41ef13e0..d8097750 100644 --- a/docs/reference/bootstrap_unnest_tbl.html +++ b/docs/reference/bootstrap_unnest_tbl.html @@ -105,16 +105,16 @@

    Examples#> # A tibble: 50,000 × 2 #> sim_number y #> <fct> <dbl> -#> 1 1 15.8 -#> 2 1 30.4 -#> 3 1 19.7 -#> 4 1 15.8 -#> 5 1 19.2 +#> 1 1 15.2 +#> 2 1 26 +#> 3 1 14.3 +#> 4 1 17.8 +#> 5 1 15.5 #> 6 1 14.7 -#> 7 1 14.3 -#> 8 1 10.4 -#> 9 1 17.8 -#> 10 1 15 +#> 7 1 21.4 +#> 8 1 15.2 +#> 9 1 30.4 +#> 10 1 30.4 #> # … with 49,990 more rows bootstrap_unnest_tbl(tb) %>% @@ -122,16 +122,16 @@

    Examples#> # A tibble: 2,000 × 13 #> sim_num…¹ mean_…² media…³ std_val min_val max_val skewn…⁴ kurto…⁵ range iqr #> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 18.1 17.8 5.38 10.4 30.4 0.824 3.37 20 5 -#> 2 2 20.6 21 6.86 10.4 32.4 0.301 2.16 22 8.6 -#> 3 3 19.5 19.2 5.87 10.4 33.9 0.816 3.34 23.5 5.9 -#> 4 4 19.5 21 5.52 10.4 33.9 0.255 3.33 23.5 6.3 -#> 5 5 19.8 18.1 6.70 10.4 33.9 0.906 2.75 23.5 9.2 -#> 6 6 18.0 16.4 5.66 10.4 33.9 1.06 4.22 23.5 6.7 -#> 7 7 19.8 18.1 6.83 10.4 33.9 0.833 2.78 23.5 6.8 -#> 8 8 18.7 17.8 5.46 10.4 32.4 0.935 3.54 22 5.8 -#> 9 9 19.0 19.2 5.35 10.4 33.9 0.694 3.74 23.5 6.4 -#> 10 10 20.7 21 5.62 13.3 30.4 0.396 1.99 17.1 6.4 +#> 1 1 20.7 21 5.65 10.4 30.4 0.375 2.32 20 7 +#> 2 2 17.1 17.3 3.97 10.4 26 -0.157 2.76 15.6 4 +#> 3 3 17.9 18.1 4.26 10.4 30.4 0.979 4.54 20 4.7 +#> 4 4 20.2 18.7 6.57 10.4 33.9 0.710 2.46 23.5 9.2 +#> 5 5 22.6 21.4 6.97 10.4 33.9 0.247 2.02 23.5 9.5 +#> 6 6 17.7 15.8 4.80 10.4 30.4 0.782 3.33 20 6.4 +#> 7 7 20.1 18.7 6.18 10.4 32.4 0.621 2.29 22 9.4 +#> 8 8 20.5 19.2 6.32 10.4 33.9 0.694 2.66 23.5 8.9 +#> 9 9 20.1 19.2 6.15 10.4 32.4 0.749 2.62 22 6.2 +#> 10 10 19.3 18.7 5.89 10.4 33.9 0.723 3.59 23.5 5.6 #> # … with 1,990 more rows, 3 more variables: variance <dbl>, ci_low <dbl>, #> # ci_high <dbl>, and abbreviated variable names ¹​sim_number, ²​mean_val, #> # ³​median_val, ⁴​skewness, ⁵​kurtosis diff --git a/docs/reference/tidy_autoplot-1.png b/docs/reference/tidy_autoplot-1.png index aa902557..625f383b 100644 Binary files a/docs/reference/tidy_autoplot-1.png and b/docs/reference/tidy_autoplot-1.png differ diff --git a/docs/reference/tidy_autoplot-2.png b/docs/reference/tidy_autoplot-2.png index 3bdaf098..c4d9cb26 100644 Binary files a/docs/reference/tidy_autoplot-2.png and b/docs/reference/tidy_autoplot-2.png differ diff --git a/docs/reference/tidy_bernoulli.html b/docs/reference/tidy_bernoulli.html index a18254e5..ac91f9c0 100644 --- a/docs/reference/tidy_bernoulli.html +++ b/docs/reference/tidy_bernoulli.html @@ -156,18 +156,18 @@

    Author<

    Examples

    tidy_bernoulli()
 #> # A tibble: 50 × 7
-#>    sim_number     x     y      dx     dy     p     q
-#>    <fct>      <int> <int>   <dbl>  <dbl> <dbl> <dbl>
-#>  1 1              1     1 -0.405  0.0292   1       1
-#>  2 1              2     0 -0.368  0.0637   0.9     0
-#>  3 1              3     0 -0.331  0.129    0.9     0
-#>  4 1              4     0 -0.294  0.243    0.9     0
-#>  5 1              5     0 -0.258  0.424    0.9     0
-#>  6 1              6     0 -0.221  0.688    0.9     0
-#>  7 1              7     1 -0.184  1.03     1       1
-#>  8 1              8     0 -0.147  1.44     0.9     0
-#>  9 1              9     0 -0.110  1.87     0.9     0
-#> 10 1             10     0 -0.0727 2.25     0.9     0
+#>    sim_number     x     y       dx     dy     p     q
+#>    <fct>      <int> <int>    <dbl>  <dbl> <dbl> <dbl>
+#>  1 1              1     0 -0.296   0.0427   0.9     0
+#>  2 1              2     0 -0.264   0.108    0.9     0
+#>  3 1              3     1 -0.231   0.247    1       1
+#>  4 1              4     0 -0.199   0.504    0.9     0
+#>  5 1              5     0 -0.166   0.924    0.9     0
+#>  6 1              6     0 -0.134   1.52     0.9     0
+#>  7 1              7     0 -0.101   2.25     0.9     0
+#>  8 1              8     0 -0.0687  2.98     0.9     0
+#>  9 1              9     0 -0.0362  3.55     0.9     0
+#> 10 1             10     0 -0.00372 3.79     0.9     0
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_beta.html b/docs/reference/tidy_beta.html index 07e9b8f8..b63cecd7 100644 --- a/docs/reference/tidy_beta.html +++ b/docs/reference/tidy_beta.html @@ -182,18 +182,18 @@

    Author<

    Examples

    tidy_beta()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y      dx      dy      p      q
-#>    <fct>      <int>  <dbl>   <dbl>   <dbl>  <dbl>  <dbl>
-#>  1 1              1 0.741  -0.366  0.00468 0      0.791 
-#>  2 1              2 0.0505 -0.332  0.0107  0.0204 0.0435
-#>  3 1              3 0.737  -0.297  0.0228  0.0408 0.786 
-#>  4 1              4 0.398  -0.263  0.0452  0.0612 0.419 
-#>  5 1              5 0.193  -0.229  0.0835  0.0816 0.198 
-#>  6 1              6 0.661  -0.195  0.144   0.102  0.704 
-#>  7 1              7 0.701  -0.161  0.231   0.122  0.747 
-#>  8 1              8 0.533  -0.126  0.347   0.143  0.566 
-#>  9 1              9 0.543  -0.0922 0.486   0.163  0.577 
-#> 10 1             10 0.0287 -0.0580 0.638   0.184  0.0199
+#>    sim_number     x     y      dx      dy      p     q
+#>    <fct>      <int> <dbl>   <dbl>   <dbl>  <dbl> <dbl>
+#>  1 1              1 0.240 -0.340  0.00181 0      0.254
+#>  2 1              2 0.157 -0.307  0.00429 0.0204 0.166
+#>  3 1              3 0.565 -0.274  0.00942 0.0408 0.597
+#>  4 1              4 0.825 -0.241  0.0192  0.0612 0.872
+#>  5 1              5 0.765 -0.208  0.0361  0.0816 0.808
+#>  6 1              6 0.869 -0.174  0.0631  0.102  0.918
+#>  7 1              7 0.631 -0.141  0.103   0.122  0.667
+#>  8 1              8 0.315 -0.108  0.158   0.143  0.333
+#>  9 1              9 0.617 -0.0747 0.229   0.163  0.652
+#> 10 1             10 0.139 -0.0414 0.314   0.184  0.147
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_burr.html b/docs/reference/tidy_burr.html index 89a56e2d..178c8a68 100644 --- a/docs/reference/tidy_burr.html +++ b/docs/reference/tidy_burr.html @@ -190,18 +190,18 @@

    Author<

    Examples

    tidy_burr()
 #> # A tibble: 50 × 7
-#>    sim_number     x       y      dx      dy      p          q
-#>    <fct>      <int>   <dbl>   <dbl>   <dbl>  <dbl>      <dbl>
-#>  1 1              1 34.6    -2.48   0.00109 0      Inf       
-#>  2 1              2  0.0280 -1.68   0.0150  0.0200   0.000571
-#>  3 1              3  0.962  -0.867  0.0855  0.0392   0.0283  
-#>  4 1              4  0.204  -0.0587 0.215   0.0577   0.00567 
-#>  5 1              5  3.08    0.749  0.266   0.0755   0.0974  
-#>  6 1              6  0.727   1.56   0.196   0.0926   0.0212  
-#>  7 1              7  1.54    2.37   0.104   0.109    0.0462  
-#>  8 1              8  0.593   3.17   0.0441  0.125    0.0172  
-#>  9 1              9  0.0464  3.98   0.0161  0.140    0.00110 
-#> 10 1             10  1.06    4.79   0.0167  0.155    0.0313  
+#>    sim_number     x      y    dx           dy      p        q
+#>    <fct>      <int>  <dbl> <dbl>        <dbl>  <dbl>    <dbl>
+#>  1 1              1  2.13  -4.89 0.00107      0      0.00569 
+#>  2 1              2  0.325  2.98 0.0840       0.0200 0.000845
+#>  3 1              3  0.756 10.8  0.00853      0.0392 0.00199 
+#>  4 1              4  0.225 18.7  0.00426      0.0577 0.000579
+#>  5 1              5  0.278 26.6  0.00380      0.0755 0.000719
+#>  6 1              6 33.9   34.5  0.0133       0.0926 0.0990  
+#>  7 1              7  3.10  42.3  0.00446      0.109  0.00830 
+#>  8 1              8 41.7   50.2  0.0000000125 0.125  0.125   
+#>  9 1              9  0.447 58.1  0            0.140  0.00117 
+#> 10 1             10  1.81  65.9  0            0.155  0.00481 
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_cauchy.html b/docs/reference/tidy_cauchy.html index 79b4c2dd..4b68228e 100644 --- a/docs/reference/tidy_cauchy.html +++ b/docs/reference/tidy_cauchy.html @@ -176,18 +176,18 @@

    Author<

    Examples

    tidy_cauchy()
 #> # A tibble: 50 × 7
-#>    sim_number     x        y    dx       dy     p      q
-#>    <fct>      <int>    <dbl> <dbl>    <dbl> <dbl>  <dbl>
-#>  1 1              1 -10.3    -130. 2.19e- 4 0.5     1.87
-#>  2 1              2  11.7    -127. 2.80e- 3 0.506 Inf   
-#>  3 1              3  -0.0993 -124. 1.77e-11 0.513   3.71
-#>  4 1              4  -1.72   -121. 3.54e-18 0.519   3.23
-#>  5 1              5  -0.613  -118. 0        0.526   3.54
-#>  6 1              6   0.983  -116. 7.11e-18 0.532   4.10
-#>  7 1              7   0.0567 -113. 2.37e-18 0.539   3.76
-#>  8 1              8   1.64   -110. 3.69e-18 0.545   4.38
-#>  9 1              9   0.0626 -107. 1.63e-18 0.552   3.76
-#> 10 1             10  -1.28   -104. 0        0.558   3.35
+#>    sim_number     x       y    dx       dy     p       q
+#>    <fct>      <int>   <dbl> <dbl>    <dbl> <dbl>   <dbl>
+#>  1 1              1  0.957  -23.7 2.14e- 4 0.5     0.656
+#>  2 1              2  0.141  -22.9 7.60e- 3 0.506   0.553
+#>  3 1              3  1.30   -22.2 1.67e- 2 0.513   0.702
+#>  4 1              4 -0.385  -21.4 2.22e- 3 0.519   0.491
+#>  5 1              5  1.17   -20.7 1.84e- 5 0.526   0.685
+#>  6 1              6  1.56   -19.9 8.65e- 9 0.532   0.738
+#>  7 1              7  0.529  -19.2 2.87e-13 0.539   0.601
+#>  8 1              8 11.7    -18.4 1.26e-17 0.545 Inf    
+#>  9 1              9 -0.0820 -17.7 5.45e-19 0.552   0.526
+#> 10 1             10 -1.25   -16.9 0        0.558   0.396
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_chisquare.html b/docs/reference/tidy_chisquare.html index 072d2f6c..a1eb100b 100644 --- a/docs/reference/tidy_chisquare.html +++ b/docs/reference/tidy_chisquare.html @@ -175,18 +175,18 @@

    Author<

    Examples

    tidy_chisquare()
 #> # A tibble: 50 × 7
-#>    sim_number     x        y      dx      dy      p             q
-#>    <fct>      <int>    <dbl>   <dbl>   <dbl>  <dbl>         <dbl>
-#>  1 1              1 3.68     -2.25   0.00129 0      0.272        
-#>  2 1              2 4.08     -1.86   0.00557 0.0691 0.336        
-#>  3 1              3 0.259    -1.47   0.0186  0.0978 0.00135      
-#>  4 1              4 0.0142   -1.08   0.0483  0.120  0.00000367   
-#>  5 1              5 0.00115  -0.692  0.0984  0.138  0.00000000371
-#>  6 1              6 5.58     -0.303  0.160   0.155  0.635        
-#>  7 1              7 0.000721  0.0860 0.213   0.169  0            
-#>  8 1              8 0.0168    0.475  0.240   0.183  0.00000521   
-#>  9 1              9 0.940     0.864  0.240   0.195  0.0178       
-#> 10 1             10 2.43      1.25   0.225   0.207  0.119        
+#>    sim_number     x     y     dx      dy      p        q
+#>    <fct>      <int> <dbl>  <dbl>   <dbl>  <dbl>    <dbl>
+#>  1 1              1 4.56  -3.13  0.00110 0      0.631   
+#>  2 1              2 0.905 -2.76  0.00313 0.0691 0.0245  
+#>  3 1              3 1.40  -2.39  0.00787 0.0978 0.0589  
+#>  4 1              4 0.813 -2.02  0.0176  0.120  0.0198  
+#>  5 1              5 1.70  -1.65  0.0348  0.138  0.0869  
+#>  6 1              6 6.49  -1.27  0.0615  0.155  1.32    
+#>  7 1              7 2.28  -0.902 0.0969  0.169  0.156   
+#>  8 1              8 0.129 -0.531 0.136   0.183  0.000495
+#>  9 1              9 0.603 -0.159 0.173   0.195  0.0109  
+#> 10 1             10 6.31   0.212 0.197   0.207  1.24    
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_combine_distributions.html b/docs/reference/tidy_combine_distributions.html index 8f7708e7..dcf64034 100644 --- a/docs/reference/tidy_combine_distributions.html +++ b/docs/reference/tidy_combine_distributions.html @@ -115,16 +115,16 @@

    Examples#> # A tibble: 150 × 8 #> sim_number x y dx dy p q dist_type #> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> -#> 1 1 1 0.382 -3.62 0.000318 0.649 0.382 Gaussian c(0, 1) -#> 2 1 2 -0.922 -3.47 0.000889 0.178 -0.922 Gaussian c(0, 1) -#> 3 1 3 0.289 -3.33 0.00220 0.614 0.289 Gaussian c(0, 1) -#> 4 1 4 1.49 -3.19 0.00484 0.931 1.49 Gaussian c(0, 1) -#> 5 1 5 0.268 -3.04 0.00948 0.606 0.268 Gaussian c(0, 1) -#> 6 1 6 0.557 -2.90 0.0166 0.711 0.557 Gaussian c(0, 1) -#> 7 1 7 -1.53 -2.76 0.0260 0.0626 -1.53 Gaussian c(0, 1) -#> 8 1 8 1.53 -2.62 0.0369 0.937 1.53 Gaussian c(0, 1) -#> 9 1 9 0.361 -2.47 0.0482 0.641 0.361 Gaussian c(0, 1) -#> 10 1 10 -1.37 -2.33 0.0591 0.0850 -1.37 Gaussian c(0, 1) +#> 1 1 1 -0.459 -3.12 0.000257 0.323 -0.459 Gaussian c(0, 1) +#> 2 1 2 -0.224 -2.99 0.000695 0.411 -0.224 Gaussian c(0, 1) +#> 3 1 3 0.380 -2.87 0.00168 0.648 0.380 Gaussian c(0, 1) +#> 4 1 4 1.95 -2.74 0.00365 0.975 1.95 Gaussian c(0, 1) +#> 5 1 5 -1.48 -2.61 0.00714 0.0699 -1.48 Gaussian c(0, 1) +#> 6 1 6 -0.532 -2.49 0.0127 0.297 -0.532 Gaussian c(0, 1) +#> 7 1 7 1.83 -2.36 0.0208 0.966 1.83 Gaussian c(0, 1) +#> 8 1 8 1.19 -2.24 0.0315 0.884 1.19 Gaussian c(0, 1) +#> 9 1 9 0.230 -2.11 0.0449 0.591 0.230 Gaussian c(0, 1) +#> 10 1 10 0.620 -1.99 0.0604 0.732 0.620 Gaussian c(0, 1) #> # … with 140 more rows ## OR @@ -138,16 +138,16 @@

    Examples#> # A tibble: 200 × 8 #> sim_number x y dx dy p q dist_type #> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> -#> 1 1 1 -1.28 -3.43 0.000308 0.0995 -1.28 Gaussian c(0, 1) -#> 2 1 2 -0.904 -3.28 0.000847 0.183 -0.904 Gaussian c(0, 1) -#> 3 1 3 1.30 -3.12 0.00209 0.903 1.30 Gaussian c(0, 1) -#> 4 1 4 -0.826 -2.97 0.00463 0.204 -0.826 Gaussian c(0, 1) -#> 5 1 5 0.410 -2.81 0.00926 0.659 0.410 Gaussian c(0, 1) -#> 6 1 6 0.456 -2.66 0.0167 0.676 0.456 Gaussian c(0, 1) -#> 7 1 7 0.783 -2.50 0.0275 0.783 0.783 Gaussian c(0, 1) -#> 8 1 8 -1.02 -2.35 0.0413 0.154 -1.02 Gaussian c(0, 1) -#> 9 1 9 1.50 -2.20 0.0577 0.934 1.50 Gaussian c(0, 1) -#> 10 1 10 -0.772 -2.04 0.0759 0.220 -0.772 Gaussian c(0, 1) +#> 1 1 1 1.34 -4.01 0.000181 0.910 1.34 Gaussian c(0, 1) +#> 2 1 2 0.625 -3.83 0.000508 0.734 0.625 Gaussian c(0, 1) +#> 3 1 3 1.69 -3.64 0.00126 0.954 1.69 Gaussian c(0, 1) +#> 4 1 4 -0.331 -3.46 0.00281 0.370 -0.331 Gaussian c(0, 1) +#> 5 1 5 1.14 -3.27 0.00559 0.874 1.14 Gaussian c(0, 1) +#> 6 1 6 -0.391 -3.08 0.0101 0.348 -0.391 Gaussian c(0, 1) +#> 7 1 7 1.95 -2.90 0.0167 0.974 1.95 Gaussian c(0, 1) +#> 8 1 8 -1.90 -2.71 0.0256 0.0286 -1.90 Gaussian c(0, 1) +#> 9 1 9 -1.85 -2.52 0.0372 0.0320 -1.85 Gaussian c(0, 1) +#> 10 1 10 -1.19 -2.34 0.0516 0.116 -1.19 Gaussian c(0, 1) #> # … with 190 more rows diff --git a/docs/reference/tidy_combined_autoplot-1.png b/docs/reference/tidy_combined_autoplot-1.png index 5e8fe6f8..fbb06a3f 100644 Binary files a/docs/reference/tidy_combined_autoplot-1.png and b/docs/reference/tidy_combined_autoplot-1.png differ diff --git a/docs/reference/tidy_combined_autoplot-2.png b/docs/reference/tidy_combined_autoplot-2.png index e7cfa8a5..299055d7 100644 Binary files a/docs/reference/tidy_combined_autoplot-2.png and b/docs/reference/tidy_combined_autoplot-2.png differ diff --git a/docs/reference/tidy_combined_autoplot.html b/docs/reference/tidy_combined_autoplot.html index ac18e1f7..bd146bfa 100644 --- a/docs/reference/tidy_combined_autoplot.html +++ b/docs/reference/tidy_combined_autoplot.html @@ -182,18 +182,18 @@

    Examples combined_tbl #> # A tibble: 150 × 8 -#> sim_number x y dx dy p q dist_type -#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> -#> 1 1 1 -0.310 -3.77 0.000266 0.378 -0.310 Gaussian c(0, 1) -#> 2 1 2 -0.231 -3.61 0.000822 0.409 -0.231 Gaussian c(0, 1) -#> 3 1 3 -0.440 -3.45 0.00220 0.330 -0.440 Gaussian c(0, 1) -#> 4 1 4 -0.277 -3.29 0.00509 0.391 -0.277 Gaussian c(0, 1) -#> 5 1 5 0.627 -3.13 0.0103 0.735 0.627 Gaussian c(0, 1) -#> 6 1 6 -0.370 -2.98 0.0181 0.356 -0.370 Gaussian c(0, 1) -#> 7 1 7 -0.660 -2.82 0.0283 0.255 -0.660 Gaussian c(0, 1) -#> 8 1 8 -2.55 -2.66 0.0396 0.00539 -2.55 Gaussian c(0, 1) -#> 9 1 9 -1.46 -2.50 0.0510 0.0720 -1.46 Gaussian c(0, 1) -#> 10 1 10 1.18 -2.34 0.0624 0.880 1.18 Gaussian c(0, 1) +#> sim_number x y dx dy p q dist_type +#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> +#> 1 1 1 0.275 -4.15 0.000206 0.608 0.275 Gaussian c(0, 1) +#> 2 1 2 1.27 -3.99 0.000583 0.898 1.27 Gaussian c(0, 1) +#> 3 1 3 -0.267 -3.83 0.00144 0.395 -0.267 Gaussian c(0, 1) +#> 4 1 4 -1.43 -3.67 0.00312 0.0765 -1.43 Gaussian c(0, 1) +#> 5 1 5 -0.464 -3.51 0.00594 0.321 -0.464 Gaussian c(0, 1) +#> 6 1 6 -1.91 -3.34 0.00997 0.0283 -1.91 Gaussian c(0, 1) +#> 7 1 7 -0.644 -3.18 0.0150 0.260 -0.644 Gaussian c(0, 1) +#> 8 1 8 -1.52 -3.02 0.0204 0.0638 -1.52 Gaussian c(0, 1) +#> 9 1 9 1.14 -2.86 0.0263 0.874 1.14 Gaussian c(0, 1) +#> 10 1 10 -0.441 -2.70 0.0335 0.329 -0.441 Gaussian c(0, 1) #> # … with 140 more rows combined_tbl %>% diff --git a/docs/reference/tidy_distribution_comparison.html b/docs/reference/tidy_distribution_comparison.html index fee1deec..890e29a1 100644 --- a/docs/reference/tidy_distribution_comparison.html +++ b/docs/reference/tidy_distribution_comparison.html @@ -155,80 +155,80 @@

    Examples#> #> $deviance_tbl #> # A tibble: 352 × 2 -#> name value -#> <chr> <dbl> -#> 1 Empirical 0.451 -#> 2 Beta c(1.11, 1.58, 0) 0.140 -#> 3 Cauchy c(19.2, 7.38) 0.287 -#> 4 Exponential c(0.05) 0.399 -#> 5 Gamma c(11.47, 1.75) -0.545 -#> 6 Logistic c(20.09, 3.27) 0.0144 -#> 7 Lognormal c(2.96, 0.29) -0.126 -#> 8 Pareto c(10.4, 1.62) 0.412 -#> 9 Uniform c(8.34, 31.84) -0.150 -#> 10 Weibull c(3.58, 22.29) 0.00581 +#> name value +#> <chr> <dbl> +#> 1 Empirical 0.451 +#> 2 Beta c(1.11, 1.58, 0) 0.145 +#> 3 Cauchy c(19.2, 7.38) -0.549 +#> 4 Exponential c(0.05) 0.301 +#> 5 Gamma c(11.47, 1.75) 0.451 +#> 6 Logistic c(20.09, 3.27) -0.0963 +#> 7 Lognormal c(2.96, 0.29) -0.0212 +#> 8 Pareto c(10.4, 1.62) 0.427 +#> 9 Uniform c(8.34, 31.84) -0.160 +#> 10 Weibull c(3.58, 22.29) -0.259 #> # … with 342 more rows #> #> $total_deviance_tbl #> # A tibble: 10 × 2 #> dist_with_params abs_tot_deviance #> <chr> <dbl> -#> 1 Gaussian c(20.09, 5.93) 0.0168 -#> 2 Logistic c(20.09, 3.27) 0.0168 -#> 3 Beta c(1.11, 1.58, 0) 0.219 -#> 4 Gamma c(11.47, 1.75) 2.13 -#> 5 Lognormal c(2.96, 0.29) 2.68 -#> 6 Weibull c(3.58, 22.29) 3.09 -#> 7 Uniform c(8.34, 31.84) 4.30 -#> 8 Exponential c(0.05) 5.67 -#> 9 Cauchy c(19.2, 7.38) 7.40 -#> 10 Pareto c(10.4, 1.62) 8.06 +#> 1 Cauchy c(19.2, 7.38) 0.181 +#> 2 Beta c(1.11, 1.58, 0) 1.11 +#> 3 Uniform c(8.34, 31.84) 2.58 +#> 4 Weibull c(3.58, 22.29) 3.68 +#> 5 Gamma c(11.47, 1.75) 3.88 +#> 6 Lognormal c(2.96, 0.29) 4.81 +#> 7 Gaussian c(20.09, 5.93) 6.03 +#> 8 Pareto c(10.4, 1.62) 6.69 +#> 9 Exponential c(0.05) 7.20 +#> 10 Logistic c(20.09, 3.27) 8.75 #> #> $aic_tbl #> # A tibble: 10 × 3 #> dist_type aic_value abs_aic #> <fct> <dbl> <dbl> -#> 1 Beta c(1.11, 1.58, 0) -39.0 39.0 -#> 2 Pareto c(10.4, 1.62) 86.6 86.6 -#> 3 Uniform c(8.34, 31.84) -189. 189. -#> 4 Lognormal c(2.96, 0.29) -189. 189. -#> 5 Weibull c(3.58, 22.29) -202. 202. -#> 6 Gamma c(11.47, 1.75) -229. 229. -#> 7 Logistic c(20.09, 3.27) -230. 230. -#> 8 Gaussian c(20.09, 5.93) -233. 233. -#> 9 Cauchy c(19.2, 7.38) -234. 234. -#> 10 Exponential c(0.05) -243. 243. +#> 1 Beta c(1.11, 1.58, 0) -3.22 3.22 +#> 2 Pareto c(10.4, 1.62) 79.9 79.9 +#> 3 Logistic c(20.09, 3.27) -139. 139. +#> 4 Gaussian c(20.09, 5.93) -144. 144. +#> 5 Lognormal c(2.96, 0.29) -157. 157. +#> 6 Gamma c(11.47, 1.75) -176. 176. +#> 7 Weibull c(3.58, 22.29) -177. 177. +#> 8 Uniform c(8.34, 31.84) -180. 180. +#> 9 Exponential c(0.05) -196. 196. +#> 10 Cauchy c(19.2, 7.38) -279. 279. #> #> $kolmogorov_smirnov_tbl #> # A tibble: 10 × 6 #> dist_type ks_statistic ks_pvalue ks_method alter…¹ dist_…² #> <fct> <dbl> <dbl> <chr> <chr> <chr> #> 1 Beta c(1.11, 1.58, 0) 0.781 0.000500 Monte-Carlo t… two-si… Beta c… -#> 2 Cauchy c(19.2, 7.38) 0.75 0.000500 Monte-Carlo t… two-si… Cauchy… -#> 3 Exponential c(0.05) 0.5 0.00100 Monte-Carlo t… two-si… Expone… -#> 4 Gamma c(11.47, 1.75) 0.125 0.968 Monte-Carlo t… two-si… Gamma … -#> 5 Logistic c(20.09, 3.27) 0.281 0.158 Monte-Carlo t… two-si… Logist… -#> 6 Lognormal c(2.96, 0.29) 0.125 0.971 Monte-Carlo t… two-si… Lognor… -#> 7 Pareto c(10.4, 1.62) 0.688 0.000500 Monte-Carlo t… two-si… Pareto… -#> 8 Uniform c(8.34, 31.84) 0.25 0.270 Monte-Carlo t… two-si… Unifor… -#> 9 Weibull c(3.58, 22.29) 0.188 0.637 Monte-Carlo t… two-si… Weibul… -#> 10 Gaussian c(20.09, 5.93) 0.156 0.824 Monte-Carlo t… two-si… Gaussi… +#> 2 Cauchy c(19.2, 7.38) 0.531 0.000500 Monte-Carlo t… two-si… Cauchy… +#> 3 Exponential c(0.05) 0.438 0.00400 Monte-Carlo t… two-si… Expone… +#> 4 Gamma c(11.47, 1.75) 0.188 0.651 Monte-Carlo t… two-si… Gamma … +#> 5 Logistic c(20.09, 3.27) 0.219 0.417 Monte-Carlo t… two-si… Logist… +#> 6 Lognormal c(2.96, 0.29) 0.156 0.843 Monte-Carlo t… two-si… Lognor… +#> 7 Pareto c(10.4, 1.62) 0.844 0.000500 Monte-Carlo t… two-si… Pareto… +#> 8 Uniform c(8.34, 31.84) 0.156 0.841 Monte-Carlo t… two-si… Unifor… +#> 9 Weibull c(3.58, 22.29) 0.188 0.642 Monte-Carlo t… two-si… Weibul… +#> 10 Gaussian c(20.09, 5.93) 0.219 0.434 Monte-Carlo t… two-si… Gaussi… #> # … with abbreviated variable names ¹​alternative, ²​dist_char #> #> $multi_metric_tbl #> # A tibble: 10 × 8 #> dist_type abs_t…¹ aic_v…² abs_aic ks_st…³ ks_pv…⁴ ks_me…⁵ alter…⁶ #> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <chr> -#> 1 Gaussian c(20.09, 5.… 0.0168 -233. 233. 0.156 8.24e-1 Monte-… two-si… -#> 2 Logistic c(20.09, 3.… 0.0168 -230. 230. 0.281 1.58e-1 Monte-… two-si… -#> 3 Beta c(1.11, 1.58, 0) 0.219 -39.0 39.0 0.781 5.00e-4 Monte-… two-si… -#> 4 Gamma c(11.47, 1.75) 2.13 -229. 229. 0.125 9.68e-1 Monte-… two-si… -#> 5 Lognormal c(2.96, 0.… 2.68 -189. 189. 0.125 9.71e-1 Monte-… two-si… -#> 6 Weibull c(3.58, 22.2… 3.09 -202. 202. 0.188 6.37e-1 Monte-… two-si… -#> 7 Uniform c(8.34, 31.8… 4.30 -189. 189. 0.25 2.70e-1 Monte-… two-si… -#> 8 Exponential c(0.05) 5.67 -243. 243. 0.5 1.00e-3 Monte-… two-si… -#> 9 Cauchy c(19.2, 7.38) 7.40 -234. 234. 0.75 5.00e-4 Monte-… two-si… -#> 10 Pareto c(10.4, 1.62) 8.06 86.6 86.6 0.688 5.00e-4 Monte-… two-si… +#> 1 Cauchy c(19.2, 7.38) 0.181 -279. 279. 0.531 5.00e-4 Monte-… two-si… +#> 2 Beta c(1.11, 1.58, 0) 1.11 -3.22 3.22 0.781 5.00e-4 Monte-… two-si… +#> 3 Uniform c(8.34, 31.8… 2.58 -180. 180. 0.156 8.41e-1 Monte-… two-si… +#> 4 Weibull c(3.58, 22.2… 3.68 -177. 177. 0.188 6.42e-1 Monte-… two-si… +#> 5 Gamma c(11.47, 1.75) 3.88 -176. 176. 0.188 6.51e-1 Monte-… two-si… +#> 6 Lognormal c(2.96, 0.… 4.81 -157. 157. 0.156 8.43e-1 Monte-… two-si… +#> 7 Gaussian c(20.09, 5.… 6.03 -144. 144. 0.219 4.34e-1 Monte-… two-si… +#> 8 Pareto c(10.4, 1.62) 6.69 79.9 79.9 0.844 5.00e-4 Monte-… two-si… +#> 9 Exponential c(0.05) 7.20 -196. 196. 0.438 4.00e-3 Monte-… two-si… +#> 10 Logistic c(20.09, 3.… 8.75 -139. 139. 0.219 4.17e-1 Monte-… two-si… #> # … with abbreviated variable names ¹​abs_tot_deviance, ²​aic_value, #> # ³​ks_statistic, ⁴​ks_pvalue, ⁵​ks_method, ⁶​alternative #> diff --git a/docs/reference/tidy_distribution_summary_tbl.html b/docs/reference/tidy_distribution_summary_tbl.html index f2b1fde1..c08d435c 100644 --- a/docs/reference/tidy_distribution_summary_tbl.html +++ b/docs/reference/tidy_distribution_summary_tbl.html @@ -126,20 +126,21 @@

    Examples#> # A tibble: 1 × 12 #> mean_val median_…¹ std_val min_val max_val skewn…² kurto…³ range iqr varia…⁴ #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 0.0118 -0.0355 0.995 -3.12 3.57 0.144 3.73 6.70 1.26 0.989 +#> 1 -0.0127 0.0901 0.989 -2.51 2.61 -0.0150 2.75 5.13 1.28 0.978 #> # … with 2 more variables: ci_low <dbl>, ci_high <dbl>, and abbreviated #> # variable names ¹​median_val, ²​skewness, ³​kurtosis, ⁴​variance tidy_distribution_summary_tbl(tn, sim_number) #> # A tibble: 5 × 13 -#> sim_num…¹ mean_val media…² std_val min_val max_val skewn…³ kurto…⁴ range iqr -#> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 0.0466 0.0733 1.17 -2.76 3.57 0.313 3.50 6.33 1.81 -#> 2 2 -0.0584 -0.242 0.796 -1.57 1.94 0.574 2.90 3.51 1.04 -#> 3 3 -0.00559 -0.0498 1.02 -3.12 3.04 -0.0969 4.68 6.16 0.822 -#> 4 4 0.140 0.0885 0.713 -1.57 1.42 -0.150 2.33 2.98 1.11 -#> 5 5 -0.0632 -0.0256 1.20 -2.26 2.48 0.153 2.59 4.74 1.57 +#> sim_num…¹ mean_…² median…³ std_val min_val max_val skewn…⁴ kurto…⁵ range iqr +#> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 1 -0.0366 -0.0916 1.03 -2.09 2.24 -0.0411 2.38 4.34 1.39 +#> 2 2 -0.0144 0.00540 0.976 -2.42 2.21 -0.194 3.00 4.64 1.06 +#> 3 3 0.196 0.199 1.06 -2.13 2.61 0.0230 2.63 4.75 1.42 +#> 4 4 -0.109 -0.0785 0.951 -1.96 1.89 0.0450 2.16 3.85 1.48 +#> 5 5 -0.0998 0.0508 0.923 -2.51 2.28 -0.0897 3.56 4.79 0.998 #> # … with 3 more variables: variance <dbl>, ci_low <dbl>, ci_high <dbl>, and -#> # abbreviated variable names ¹​sim_number, ²​median_val, ³​skewness, ⁴​kurtosis +#> # abbreviated variable names ¹​sim_number, ²​mean_val, ³​median_val, ⁴​skewness, +#> # ⁵​kurtosis data_tbl <- tidy_combine_distributions(tn, tb) @@ -147,15 +148,15 @@

    Examples#> # A tibble: 1 × 12 #> mean_val median_…¹ std_val min_val max_val skewn…² kurto…³ range iqr varia…⁴ #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 0.260 0.318 0.775 -3.12 3.57 -0.567 5.43 6.70 0.771 0.600 +#> 1 0.230 0.330 0.767 -2.51 2.61 -0.732 4.38 5.13 0.658 0.589 #> # … with 2 more variables: ci_low <dbl>, ci_high <dbl>, and abbreviated #> # variable names ¹​median_val, ²​skewness, ³​kurtosis, ⁴​variance tidy_distribution_summary_tbl(data_tbl, dist_type) #> # A tibble: 2 × 13 #> dist_type mean_…¹ media…² std_val min_val max_val skewn…³ kurto…⁴ range iqr #> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 Gaussian… 0.0118 -0.0355 0.995 -3.12e+0 3.57 0.144 3.73 6.70 1.26 -#> 2 Beta c(1… 0.507 0.529 0.301 7.81e-4 0.999 -0.0716 1.71 0.998 0.542 +#> 1 Gaussian… -0.0127 0.0901 0.989 -2.51 2.61 -0.0150 2.75 5.13 1.28 +#> 2 Beta c(1… 0.472 0.452 0.289 0.00252 0.999 0.145 1.87 0.996 0.486 #> # … with 3 more variables: variance <dbl>, ci_low <dbl>, ci_high <dbl>, and #> # abbreviated variable names ¹​mean_val, ²​median_val, ³​skewness, ⁴​kurtosis diff --git a/docs/reference/tidy_empirical.html b/docs/reference/tidy_empirical.html index 3005cba0..5616cef9 100644 --- a/docs/reference/tidy_empirical.html +++ b/docs/reference/tidy_empirical.html @@ -121,16 +121,16 @@

    Examples#> # A tibble: 320 × 7 #> sim_number x y dx dy p q #> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 1 26 3.52 0.000124 0.844 10.4 -#> 2 1 2 17.3 4.73 0.000526 0.375 10.4 -#> 3 1 3 10.4 5.93 0.00172 0.0625 13.3 -#> 4 1 4 30.4 7.13 0.00444 0.938 13.3 -#> 5 1 5 15 8.33 0.00932 0.188 14.3 -#> 6 1 6 30.4 9.53 0.0169 0.938 14.3 -#> 7 1 7 14.7 10.7 0.0281 0.156 14.7 -#> 8 1 8 18.7 11.9 0.0437 0.469 14.7 -#> 9 1 9 33.9 13.1 0.0615 1 15 -#> 10 1 10 10.4 14.3 0.0749 0.0625 15 +#> 1 1 1 15 6.83 0.000309 0.188 13.3 +#> 2 1 2 17.8 7.91 0.00130 0.406 13.3 +#> 3 1 3 13.3 8.99 0.00436 0.0938 13.3 +#> 4 1 4 14.3 10.1 0.0117 0.125 13.3 +#> 5 1 5 13.3 11.2 0.0251 0.0938 14.3 +#> 6 1 6 19.2 12.2 0.0437 0.531 14.7 +#> 7 1 7 21.4 13.3 0.0623 0.688 14.7 +#> 8 1 8 21 14.4 0.0740 0.625 15 +#> 9 1 9 21.5 15.5 0.0759 0.719 15 +#> 10 1 10 15.2 16.6 0.0716 0.25 15 #> # … with 310 more rows diff --git a/docs/reference/tidy_exponential.html b/docs/reference/tidy_exponential.html index ee71b539..8bfdab82 100644 --- a/docs/reference/tidy_exponential.html +++ b/docs/reference/tidy_exponential.html @@ -173,18 +173,18 @@

    Author<

    Examples

    tidy_exponential()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y      dx      dy      p         q
-#>    <fct>      <int>  <dbl>   <dbl>   <dbl>  <dbl>     <dbl>
-#>  1 1              1 0.737  -0.970  0.00143 0        0.291  
-#>  2 1              2 0.0211 -0.871  0.00361 0.0202   0.00537
-#>  3 1              3 0.575  -0.772  0.00840 0.0400   0.219  
-#>  4 1              4 2.90   -0.673  0.0179  0.0594 Inf      
-#>  5 1              5 0.170  -0.574  0.0353  0.0784   0.0585 
-#>  6 1              6 0.0354 -0.475  0.0639  0.0970   0.0104 
-#>  7 1              7 0.112  -0.376  0.107   0.115    0.0375 
-#>  8 1              8 1.98   -0.277  0.166   0.133    1.15   
-#>  9 1              9 0.872  -0.178  0.239   0.151    0.355  
-#> 10 1             10 0.492  -0.0795 0.321   0.168    0.184  
+#>    sim_number     x       y      dx      dy      p      q
+#>    <fct>      <int>   <dbl>   <dbl>   <dbl>  <dbl>  <dbl>
+#>  1 1              1 0.761   -0.900  0.00101 0      0.173 
+#>  2 1              2 3.93    -0.766  0.00399 0.0202 1.76  
+#>  3 1              3 0.153   -0.633  0.0132  0.0400 0.0308
+#>  4 1              4 0.00963 -0.499  0.0367  0.0594 0     
+#>  5 1              5 0.220   -0.365  0.0863  0.0784 0.0455
+#>  6 1              6 2.40    -0.231  0.172   0.0970 0.704 
+#>  7 1              7 0.970   -0.0976 0.294   0.115  0.227 
+#>  8 1              8 0.475    0.0362 0.432   0.133  0.104 
+#>  9 1              9 3.34     0.170  0.552   0.151  1.21  
+#> 10 1             10 0.698    0.304  0.623   0.168  0.157 
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_f.html b/docs/reference/tidy_f.html index b0cca50f..e9d56888 100644 --- a/docs/reference/tidy_f.html +++ b/docs/reference/tidy_f.html @@ -179,18 +179,18 @@

    Author<

    Examples

    tidy_f()
 #> # A tibble: 50 × 7
-#>    sim_number     x       y     dx            dy      p           q
-#>    <fct>      <int>   <dbl>  <dbl>         <dbl>  <dbl>       <dbl>
-#>  1 1              1   0.425 -12.4  0.000536      0      0.000000483
-#>  2 1              2 147.      7.69 0.0274        0.0903 0.0603     
-#>  3 1              3  15.8    27.8  0.000342      0.127  0.000666   
-#>  4 1              4  13.7    47.9  0.000815      0.154  0.000502   
-#>  5 1              5  39.9    68.0  0.000000236   0.177  0.00427    
-#>  6 1              6  16.1    88.1  0.00170       0.197  0.000697   
-#>  7 1              7   5.32  108.   0.00252       0.214  0.0000758  
-#>  8 1              8   0.638 128.   0.0000866     0.230  0.00000109 
-#>  9 1              9   2.74  148.   0.00180       0.244  0.0000201  
-#> 10 1             10 111.    168.   0.00000000771 0.258  0.0338     
+#>    sim_number     x          y      dx       dy      p          q
+#>    <fct>      <int>      <dbl>   <dbl>    <dbl>  <dbl>      <dbl>
+#>  1 1              1     0.0596   -4.14 1.15e- 1 0        7.51e-11
+#>  2 1              2   111.      210.   8.13e-19 0.0903   2.79e- 4
+#>  3 1              3     0.378   423.   0        0.127    3.18e- 9
+#>  4 1              4  1072.      637.   0        0.154    2.63e- 2
+#>  5 1              5   350.      851.   0        0.177    2.76e- 3
+#>  6 1              6   279.     1065.   2.53e- 3 0.197    1.75e- 3
+#>  7 1              7     5.11   1278.   4.42e-19 0.214    5.87e- 7
+#>  8 1              8    41.9    1492.   0        0.230    3.95e- 5
+#>  9 1              9     0.954  1706.   0        0.244    2.04e- 8
+#> 10 1             10 10466.     1920.   1.04e-18 0.258  Inf       
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_four_autoplot-1.png b/docs/reference/tidy_four_autoplot-1.png index 5d868daa..87caef99 100644 Binary files a/docs/reference/tidy_four_autoplot-1.png and b/docs/reference/tidy_four_autoplot-1.png differ diff --git a/docs/reference/tidy_gamma.html b/docs/reference/tidy_gamma.html index b7d297c7..ce5c3ce9 100644 --- a/docs/reference/tidy_gamma.html +++ b/docs/reference/tidy_gamma.html @@ -179,18 +179,18 @@

    Author<

    Examples

    tidy_gamma()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y       dx      dy      p       q
-#>    <fct>      <int>  <dbl>    <dbl>   <dbl>  <dbl>   <dbl>
-#>  1 1              1 0.0195 -0.239   0.00589 0      0.00340
-#>  2 1              2 0.578  -0.206   0.0194  0.0658 0.212  
-#>  3 1              3 0.930  -0.173   0.0553  0.127  0.511  
-#>  4 1              4 0.0727 -0.140   0.136   0.185  0.0181 
-#>  5 1              5 0.0991 -0.107   0.291   0.238  0.0256 
-#>  6 1              6 0.139  -0.0736  0.544   0.288  0.0375 
-#>  7 1              7 0.368  -0.0405  0.901   0.335  0.116  
-#>  8 1              8 0.220  -0.00747 1.33    0.379  0.0627 
-#>  9 1              9 0.144   0.0256  1.78    0.420  0.0390 
-#> 10 1             10 0.110   0.0587  2.17    0.458  0.0287 
+#>    sim_number     x       y       dx      dy      p          q
+#>    <fct>      <int>   <dbl>    <dbl>   <dbl>  <dbl>      <dbl>
+#>  1 1              1 0.200   -0.392   0.00348 0        0.0483  
+#>  2 1              2 0.370   -0.348   0.00959 0.0658   0.0968  
+#>  3 1              3 0.644   -0.305   0.0239  0.127    0.197   
+#>  4 1              4 1.34    -0.262   0.0541  0.185  Inf       
+#>  5 1              5 0.00311 -0.218   0.111   0.238    0.000338
+#>  6 1              6 0.739   -0.175   0.209   0.288    0.241   
+#>  7 1              7 0.238   -0.132   0.357   0.335    0.0585  
+#>  8 1              8 0.150   -0.0884  0.559   0.379    0.0353  
+#>  9 1              9 0.212   -0.0451  0.806   0.420    0.0515  
+#> 10 1             10 0.633   -0.00179 1.07    0.458    0.192   
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_generalized_beta.html b/docs/reference/tidy_generalized_beta.html index 0f2b0a3b..55358d00 100644 --- a/docs/reference/tidy_generalized_beta.html +++ b/docs/reference/tidy_generalized_beta.html @@ -199,18 +199,18 @@

    Author<

    Examples

    tidy_generalized_beta()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y      dx      dy      p      q
-#>    <fct>      <int>  <dbl>   <dbl>   <dbl>  <dbl>  <dbl>
-#>  1 1              1 0.0693 -0.387  0.00207 0      0.0556
-#>  2 1              2 0.840  -0.350  0.00473 0.0204 0.845 
-#>  3 1              3 0.991  -0.314  0.0101  0.0408 1     
-#>  4 1              4 0.860  -0.278  0.0202  0.0612 0.865 
-#>  5 1              5 0.422  -0.241  0.0380  0.0816 0.417 
-#>  6 1              6 0.890  -0.205  0.0674  0.102  0.896 
-#>  7 1              7 0.985  -0.169  0.112   0.122  0.993 
-#>  8 1              8 0.368  -0.132  0.177   0.143  0.361 
-#>  9 1              9 0.932  -0.0960 0.264   0.163  0.939 
-#> 10 1             10 0.0409 -0.0597 0.373   0.184  0.0265
+#>    sim_number     x      y      dx      dy      p        q
+#>    <fct>      <int>  <dbl>   <dbl>   <dbl>  <dbl>    <dbl>
+#>  1 1              1 0.0663 -0.324  0.00470 0      0.0527  
+#>  2 1              2 0.484  -0.292  0.0110  0.0204 0.506   
+#>  3 1              3 0.556  -0.259  0.0238  0.0408 0.584   
+#>  4 1              4 0.838  -0.226  0.0477  0.0612 0.891   
+#>  5 1              5 0.0724 -0.193  0.0883  0.0816 0.0593  
+#>  6 1              6 0.0187 -0.161  0.151   0.102  0.000917
+#>  7 1              7 0.750  -0.128  0.240   0.122  0.795   
+#>  8 1              8 0.0918 -0.0951 0.354   0.143  0.0804  
+#>  9 1              9 0.341  -0.0624 0.487   0.163  0.351   
+#> 10 1             10 0.693  -0.0296 0.625   0.184  0.733   
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_generalized_pareto.html b/docs/reference/tidy_generalized_pareto.html index deaedc96..37a72ffd 100644 --- a/docs/reference/tidy_generalized_pareto.html +++ b/docs/reference/tidy_generalized_pareto.html @@ -197,18 +197,18 @@

    Author<

    Examples

    tidy_generalized_pareto()
 #> # A tibble: 50 × 7
-#>    sim_number     x       y     dx          dy      p        q
-#>    <fct>      <int>   <dbl>  <dbl>       <dbl>  <dbl>    <dbl>
-#>  1 1              1  0.525  -1.56  0.00141     0      0.0112  
-#>  2 1              2  0.403  -0.548 0.122       0.02   0.00848 
-#>  3 1              3  0.471   0.468 0.432       0.0392 0.00997 
-#>  4 1              4 15.4     1.48  0.172       0.0577 0.492   
-#>  5 1              5  1.35    2.50  0.0455      0.0755 0.0296  
-#>  6 1              6  0.793   3.52  0.0268      0.0926 0.0171  
-#>  7 1              7  0.0438  4.53  0.0189      0.109  0.000711
-#>  8 1              8  1.09    5.55  0.00902     0.125  0.0237  
-#>  9 1              9  1.31    6.56  0.000191    0.140  0.0286  
-#> 10 1             10  1.81    7.58  0.000000110 0.155  0.0402  
+#>    sim_number     x     y     dx       dy      p      q
+#>    <fct>      <int> <dbl>  <dbl>    <dbl>  <dbl>  <dbl>
+#>  1 1              1 1.63  -1.53  0.000828 0      0.0564
+#>  2 1              2 3.78  -0.846 0.0277   0.02   0.142 
+#>  3 1              3 4.32  -0.163 0.206    0.0392 0.166 
+#>  4 1              4 0.807  0.520 0.404    0.0577 0.0272
+#>  5 1              5 0.527  1.20  0.287    0.0755 0.0176
+#>  6 1              6 3.28   1.89  0.155    0.0926 0.121 
+#>  7 1              7 2.27   2.57  0.0793   0.109  0.0808
+#>  8 1              8 0.586  3.25  0.0606   0.125  0.0196
+#>  9 1              9 8.19   3.93  0.0527   0.140  0.368 
+#> 10 1             10 1.52   4.62  0.0348   0.155  0.0526
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_inverse_burr.html b/docs/reference/tidy_inverse_burr.html index 2757d840..9b1c6257 100644 --- a/docs/reference/tidy_inverse_burr.html +++ b/docs/reference/tidy_inverse_burr.html @@ -196,18 +196,18 @@

    Author<

    Examples

    tidy_inverse_burr()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y       dx       dy      p       q
-#>    <fct>      <int>  <dbl>    <dbl>    <dbl>  <dbl>   <dbl>
-#>  1 1              1 0.152  -1.51    1.50e- 3 0      0.00195
-#>  2 1              2 2.82    0.00350 3.29e- 1 0.02   0.0410 
-#>  3 1              3 2.60    1.52    2.08e- 1 0.0392 0.0377 
-#>  4 1              4 0.0858  3.04    7.55e- 2 0.0577 0.00101
-#>  5 1              5 0.555   4.56    2.09e- 2 0.0755 0.00766
-#>  6 1              6 0.142   6.07    2.91e- 3 0.0926 0.00180
-#>  7 1              7 1.73    7.59    8.38e- 3 0.109  0.0246 
-#>  8 1              8 0.118   9.11    4.40e- 6 0.125  0.00147
-#>  9 1              9 0.166  10.6     3.57e-13 0.140  0.00215
-#> 10 1             10 1.98   12.1     0        0.155  0.0284 
+#>    sim_number     x      y     dx       dy      p         q
+#>    <fct>      <int>  <dbl>  <dbl>    <dbl>  <dbl>     <dbl>
+#>  1 1              1 66.8   -1.32  0.00158  0      Inf      
+#>  2 1              2  0.319  0.100 0.354    0.02     0.00412
+#>  3 1              3  1.11   1.52  0.209    0.0392   0.0162 
+#>  4 1              4  1.41   2.94  0.0307   0.0577   0.0208 
+#>  5 1              5 11.1    4.36  0.000404 0.0755   0.198  
+#>  6 1              6  0.209  5.78  0.0205   0.0926   0.00246
+#>  7 1              7  1.15   7.19  0.0238   0.109    0.0168 
+#>  8 1              8  1.09   8.61  0.000346 0.125    0.0158 
+#>  9 1              9  2.58  10.0   0.00191  0.140    0.0394 
+#> 10 1             10 23.8   11.5   0.0286   0.155    0.551  
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_inverse_exponential.html b/docs/reference/tidy_inverse_exponential.html index 94355531..354bc947 100644 --- a/docs/reference/tidy_inverse_exponential.html +++ b/docs/reference/tidy_inverse_exponential.html @@ -183,18 +183,18 @@

    Author<

    Examples

    tidy_inverse_exponential()
 #> # A tibble: 50 × 7
-#>    sim_number     x     y     dx         dy        p     q
-#>    <fct>      <int> <dbl>  <dbl>      <dbl>    <dbl> <dbl>
-#>  1 1              1 1.56  -2.97  0.000900   0        0.232
-#>  2 1              2 0.312 -0.795 0.0809     5.24e-22 0.145
-#>  3 1              3 1.30   1.38  0.204      2.29e-11 0.221
-#>  4 1              4 0.531  3.56  0.0687     8.06e- 8 0.174
-#>  5 1              5 0.563  5.73  0.0322     4.79e- 6 0.177
-#>  6 1              6 2.94   7.91  0.0231     5.55e- 5 0.278
-#>  7 1              7 0.280 10.1   0.0205     2.84e- 4 0.138
-#>  8 1              8 0.387 12.3   0.00125    9.12e- 4 0.158
-#>  9 1              9 1.17  14.4   0.00000756 2.19e- 3 0.215
-#> 10 1             10 0.421 16.6   0.00168    4.32e- 3 0.162
+#>    sim_number     x     y     dx       dy        p      q
+#>    <fct>      <int> <dbl>  <dbl>    <dbl>    <dbl>  <dbl>
+#>  1 1              1 0.570  -1.54 4.57e- 2 0        0.125 
+#>  2 1              2 6.58   16.8  1.03e-17 5.24e-22 0.202 
+#>  3 1              3 2.38   35.2  0        2.29e-11 0.165 
+#>  4 1              4 1.74   53.6  2.26e-19 8.06e- 8 0.156 
+#>  5 1              5 0.890  71.9  4.94e- 4 4.79e- 6 0.138 
+#>  6 1              6 0.408  90.3  4.56e-19 5.55e- 5 0.114 
+#>  7 1              7 1.82  109.   0        2.84e- 4 0.157 
+#>  8 1              8 0.957 127.   0        9.12e- 4 0.139 
+#>  9 1              9 0.272 145.   2.21e-18 2.19e- 3 0.0819
+#> 10 1             10 1.33  164.   0        4.32e- 3 0.148 
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_inverse_gamma.html b/docs/reference/tidy_inverse_gamma.html index be5be7bd..6781c04e 100644 --- a/docs/reference/tidy_inverse_gamma.html +++ b/docs/reference/tidy_inverse_gamma.html @@ -193,18 +193,18 @@

    Author<

    Examples

    tidy_inverse_gamma()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y     dx       dy        p     q
-#>    <fct>      <int>  <dbl>  <dbl>    <dbl>    <dbl> <dbl>
-#>  1 1              1  6.06  -4.22  0.000609 0        0.450
-#>  2 1              2  6.07  -2.94  0.00662  5.24e-22 0.451
-#>  3 1              3 10.7   -1.66  0.0360   2.29e-11 0.612
-#>  4 1              4  1.96  -0.378 0.101    8.06e- 8 0.291
-#>  5 1              5  0.449  0.902 0.151    4.79e- 6 0.182
-#>  6 1              6  3.43   2.18  0.135    5.55e- 5 0.354
-#>  7 1              7  0.569  3.46  0.0864   2.84e- 4 0.198
-#>  8 1              8  2.63   4.74  0.0533   9.12e- 4 0.322
-#>  9 1              9  1.05   6.02  0.0365   2.19e- 3 0.239
-#> 10 1             10  0.401  7.30  0.0256   4.32e- 3 0.175
+#>    sim_number     x     y     dx      dy        p     q
+#>    <fct>      <int> <dbl>  <dbl>   <dbl>    <dbl> <dbl>
+#>  1 1              1 0.788 -0.741 0.00193 0        0.220
+#>  2 1              2 0.573  0.167 0.327   5.24e-22 0.193
+#>  3 1              3 0.341  1.07  0.449   2.29e-11 0.107
+#>  4 1              4 0.526  1.98  0.0920  8.06e- 8 0.185
+#>  5 1              5 0.978  2.89  0.0315  4.79e- 6 0.239
+#>  6 1              6 0.399  3.80  0.0305  5.55e- 5 0.153
+#>  7 1              7 8.08   4.70  0.0229  2.84e- 4 0.589
+#>  8 1              8 0.809  5.61  0.0227  9.12e- 4 0.222
+#>  9 1              9 0.458  6.52  0.0221  2.19e- 3 0.170
+#> 10 1             10 0.902  7.43  0.00619 4.32e- 3 0.232
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_inverse_normal.html b/docs/reference/tidy_inverse_normal.html index a14b02c0..504f0ef4 100644 --- a/docs/reference/tidy_inverse_normal.html +++ b/docs/reference/tidy_inverse_normal.html @@ -189,18 +189,18 @@

    Author<

    Examples

    tidy_inverse_normal()
 #> # A tibble: 50 × 7
-#>    sim_number     x     y      dx      dy        p     q
-#>    <fct>      <int> <dbl>   <dbl>   <dbl>    <dbl> <dbl>
-#>  1 1              1 2.24  -0.565  0.00122 0        0.828
-#>  2 1              2 0.516 -0.463  0.00459 6.89e-12 0.243
-#>  3 1              3 3.34  -0.362  0.0147  1.98e- 6 2.13 
-#>  4 1              4 0.518 -0.261  0.0400  1.40e- 4 0.244
-#>  5 1              5 0.678 -0.159  0.0934  1.22e- 3 0.286
-#>  6 1              6 0.312 -0.0580 0.188   4.54e- 3 0.182
-#>  7 1              7 0.616  0.0434 0.327   1.10e- 2 0.270
-#>  8 1              8 0.791  0.145  0.497   2.09e- 2 0.316
-#>  9 1              9 1.11   0.246  0.669   3.39e- 2 0.401
-#> 10 1             10 0.500  0.347  0.803   4.96e- 2 0.238
+#>    sim_number     x     y      dx      dy        p       q
+#>    <fct>      <int> <dbl>   <dbl>   <dbl>    <dbl>   <dbl>
+#>  1 1              1 4.17  -0.608  0.00152 0          3.37 
+#>  2 1              2 0.214 -0.490  0.00551 6.89e-12   0    
+#>  3 1              3 2.80  -0.373  0.0170  1.98e- 6   0.916
+#>  4 1              4 0.918 -0.256  0.0445  1.40e- 4   0.306
+#>  5 1              5 1.19  -0.139  0.0994  1.22e- 3   0.368
+#>  6 1              6 4.31  -0.0219 0.190   4.54e- 3 Inf    
+#>  7 1              7 0.437  0.0952 0.315   1.10e- 2   0.189
+#>  8 1              8 0.995  0.212  0.454   2.09e- 2   0.323
+#>  9 1              9 0.246  0.329  0.575   3.39e- 2   0.114
+#> 10 1             10 2.48   0.447  0.652   4.96e- 2   0.760
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_inverse_pareto.html b/docs/reference/tidy_inverse_pareto.html index 59cbd853..69bd8776 100644 --- a/docs/reference/tidy_inverse_pareto.html +++ b/docs/reference/tidy_inverse_pareto.html @@ -185,18 +185,18 @@

    Author<

    Examples

    tidy_inverse_pareto()
 #> # A tibble: 50 × 7
-#>    sim_number     x       y     dx       dy      p         q
-#>    <fct>      <int>   <dbl>  <dbl>    <dbl>  <dbl>     <dbl>
-#>  1 1              1  0.862  -1.71  0.00111  0      0.0149   
-#>  2 1              2  1.47   -0.474 0.126    0.02   0.0261   
-#>  3 1              3  0.372   0.761 0.349    0.0392 0.00617  
-#>  4 1              4  0.944   2.00  0.161    0.0577 0.0164   
-#>  5 1              5  0.286   3.23  0.0685   0.0755 0.00465  
-#>  6 1              6  0.0271  4.47  0.0204   0.0926 0.0000946
-#>  7 1              7  1.01    5.70  0.000918 0.109  0.0177   
-#>  8 1              8 40.9     6.94  0.00163  0.125  2.53     
-#>  9 1              9  0.245   8.17  0.0136   0.140  0.00393  
-#> 10 1             10  0.420   9.41  0.00129  0.155  0.00703  
+#>    sim_number     x      y      dx       dy      p         q
+#>    <fct>      <int>  <dbl>   <dbl>    <dbl>  <dbl>     <dbl>
+#>  1 1              1  0.709   -1.56 4.87e- 1 0      0.0000709
+#>  2 1              2  0.841  203.   1.51e-18 0.02   0.0000841
+#>  3 1              3  0.267  407.   0        0.0392 0.0000266
+#>  4 1              4  1.73   611.   1.52e-19 0.0577 0.000173 
+#>  5 1              5  0.996  815.   0        0.0755 0.0000996
+#>  6 1              6  0.541 1019.   5.69e-19 0.0926 0.0000541
+#>  7 1              7  0.261 1223.   6.01e-19 0.109  0.0000260
+#>  8 1              8  2.38  1427.   5.59e-20 0.125  0.000238 
+#>  9 1              9  0.830 1631.   0        0.140  0.0000830
+#> 10 1             10 23.5   1835.   2.69e-18 0.155  0.00236  
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_inverse_weibull.html b/docs/reference/tidy_inverse_weibull.html index dc2d8252..aec69337 100644 --- a/docs/reference/tidy_inverse_weibull.html +++ b/docs/reference/tidy_inverse_weibull.html @@ -193,18 +193,18 @@

    Author<

    Examples

    tidy_inverse_weibull()
 #> # A tibble: 50 × 7
-#>    sim_number     x        y     dx       dy        p       q
-#>    <fct>      <int>    <dbl>  <dbl>    <dbl>    <dbl>   <dbl>
-#>  1 1              1    8.19   -2.90 8.04e- 3 0          0.202
-#>  2 1              2    1.50   20.6  1.04e-14 5.24e-22   0.148
-#>  3 1              3    7.23   44.2  3.83e- 3 2.29e-11   0.197
-#>  4 1              4    0.140  67.7  9.89e-20 8.06e- 8   0    
-#>  5 1              5    2.85   91.3  0        4.79e- 6   0.165
-#>  6 1              6    6.99  115.   1.28e-18 5.55e- 5   0.195
-#>  7 1              7    0.843 138.   1.37e-19 2.84e- 4   0.135
-#>  8 1              8 1148.    162.   0        9.12e- 4 Inf    
-#>  9 1              9    1.92  185.   4.15e-19 2.19e- 3   0.155
-#> 10 1             10    0.448 209.   8.81e-21 4.32e- 3   0.122
+#>    sim_number     x      y     dx       dy        p     q
+#>    <fct>      <int>  <dbl>  <dbl>    <dbl>    <dbl> <dbl>
+#>  1 1              1  1.54  -2.90  0.000715 0        0.252
+#>  2 1              2 19.6   -1.30  0.0359   5.24e-22 0.762
+#>  3 1              3  2.06   0.300 0.199    2.29e-11 0.275
+#>  4 1              4  0.962  1.90  0.173    8.06e- 8 0.222
+#>  5 1              5  0.362  3.50  0.0635   4.79e- 6 0.170
+#>  6 1              6  1.06   5.10  0.0398   5.55e- 5 0.228
+#>  7 1              7  1.34   6.71  0.0320   2.84e- 4 0.243
+#>  8 1              8  1.21   8.31  0.0265   9.12e- 4 0.236
+#>  9 1              9  0.492  9.91  0.00490  2.19e- 3 0.186
+#> 10 1             10  2.96  11.5   0.00106  4.32e- 3 0.308
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_kurtosis_vec.html b/docs/reference/tidy_kurtosis_vec.html index 5bd254be..6ca52eac 100644 --- a/docs/reference/tidy_kurtosis_vec.html +++ b/docs/reference/tidy_kurtosis_vec.html @@ -132,7 +132,7 @@

    Author<

    Examples

    tidy_kurtosis_vec(rnorm(100, 3, 2))
-#> [1] 2.918258
+#> [1] 2.700726
    diff --git a/docs/reference/tidy_logistic.html b/docs/reference/tidy_logistic.html index 0c637c8c..aa891126 100644 --- a/docs/reference/tidy_logistic.html +++ b/docs/reference/tidy_logistic.html @@ -177,18 +177,18 @@

    Author<

    Examples

    tidy_logistic()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y    dx       dy     p        q
-#>    <fct>      <int>  <dbl> <dbl>    <dbl> <dbl>    <dbl>
-#>  1 1              1  4.79  -5.12 0.000180 0.5      1.31 
-#>  2 1              2  0.931 -4.84 0.000672 0.505   -0.371
-#>  3 1              3 -1.25  -4.55 0.00207  0.510   -1.42 
-#>  4 1              4 -3.23  -4.26 0.00533  0.515 -Inf    
-#>  5 1              5  0.225 -3.98 0.0115   0.520   -0.668
-#>  6 1              6  3.51  -3.69 0.0210   0.525    0.672
-#>  7 1              7  3.70  -3.41 0.0329   0.531    0.755
-#>  8 1              8 -0.399 -3.12 0.0453   0.536   -0.956
-#>  9 1              9  0.281 -2.84 0.0566   0.541   -0.644
-#> 10 1             10 -1.65  -2.55 0.0673   0.546   -1.70 
+#>    sim_number     x       y    dx       dy     p       q
+#>    <fct>      <int>   <dbl> <dbl>    <dbl> <dbl>   <dbl>
+#>  1 1              1 -0.259  -5.78 0.000177 0.5     0.244
+#>  2 1              2  1.31   -5.57 0.000556 0.505   1.27 
+#>  3 1              3 -0.195  -5.37 0.00148  0.510   0.281
+#>  4 1              4 -1.00   -5.16 0.00331  0.515  -0.175
+#>  5 1              5 -0.0393 -4.95 0.00627  0.520   0.371
+#>  6 1              6  0.819  -4.74 0.0101   0.525   0.904
+#>  7 1              7  1.77   -4.54 0.0136   0.531   1.69 
+#>  8 1              8  2.88   -4.33 0.0156   0.536 Inf    
+#>  9 1              9  1.23   -4.12 0.0151   0.541   1.20 
+#> 10 1             10  2.55   -3.91 0.0124   0.546   3.04 
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_lognormal.html b/docs/reference/tidy_lognormal.html index 273d89cf..31abebdb 100644 --- a/docs/reference/tidy_lognormal.html +++ b/docs/reference/tidy_lognormal.html @@ -176,18 +176,18 @@

    Author<

    Examples

    tidy_lognormal()
 #> # A tibble: 50 × 7
-#>    sim_number     x     y      dx      dy         p      q
-#>    <fct>      <int> <dbl>   <dbl>   <dbl>     <dbl>  <dbl>
-#>  1 1              1 0.143 -1.22   0.00120 0         0     
-#>  2 1              2 1.70  -0.839  0.0124  0.0000497 0.274 
-#>  3 1              3 0.162 -0.458  0.0681  0.000690  0.0478
-#>  4 1              4 1.38  -0.0774 0.205   0.00261   0.242 
-#>  5 1              5 0.631  0.303  0.355   0.00611   0.154 
-#>  6 1              6 2.48   0.684  0.397   0.0112    0.350 
-#>  7 1              7 0.221  1.06   0.352   0.0179    0.0756
-#>  8 1              8 0.326  1.45   0.287   0.0258    0.103 
-#>  9 1              9 1.29   1.83   0.204   0.0350    0.232 
-#> 10 1             10 3.30   2.21   0.131   0.0451    0.428 
+#>    sim_number     x      y     dx      dy         p        q
+#>    <fct>      <int>  <dbl>  <dbl>   <dbl>     <dbl>    <dbl>
+#>  1 1              1  0.187 -1.63  0.00124 0           0.0753
+#>  2 1              2  0.406 -1.27  0.00751 0.0000497   0.130 
+#>  3 1              3  0.187 -0.921 0.0320  0.000690    0.0752
+#>  4 1              4  1.31  -0.568 0.0971  0.00261     0.255 
+#>  5 1              5  0.447 -0.216 0.211   0.00611     0.138 
+#>  6 1              6 13.9    0.136 0.332   0.0112    Inf     
+#>  7 1              7  0.445  0.489 0.390   0.0179      0.137 
+#>  8 1              8  0.507  0.841 0.357   0.0258      0.148 
+#>  9 1              9  0.322  1.19  0.277   0.0350      0.113 
+#> 10 1             10  2.16   1.55  0.197   0.0451      0.352 
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_mixture_density-1.png b/docs/reference/tidy_mixture_density-1.png index 068e2a8a..9fe0a867 100644 Binary files a/docs/reference/tidy_mixture_density-1.png and b/docs/reference/tidy_mixture_density-1.png differ diff --git a/docs/reference/tidy_mixture_density-2.png b/docs/reference/tidy_mixture_density-2.png index c32d83ca..75efd4c3 100644 Binary files a/docs/reference/tidy_mixture_density-2.png and b/docs/reference/tidy_mixture_density-2.png differ diff --git a/docs/reference/tidy_mixture_density.html b/docs/reference/tidy_mixture_density.html index 3d7e5e60..89f728b2 100644 --- a/docs/reference/tidy_mixture_density.html +++ b/docs/reference/tidy_mixture_density.html @@ -108,68 +108,68 @@

    Examples#> # A tibble: 150 × 2 #> x y #> <int> <dbl> -#> 1 1 -0.925 -#> 2 2 0.889 -#> 3 3 -1.05 -#> 4 4 2.82 -#> 5 5 0.812 -#> 6 6 0.0362 -#> 7 7 0.312 -#> 8 8 1.10 -#> 9 9 0.522 -#> 10 10 0.0280 +#> 1 1 0.968 +#> 2 2 0.976 +#> 3 3 -0.408 +#> 4 4 -0.426 +#> 5 5 0.0215 +#> 6 6 -0.524 +#> 7 7 -0.387 +#> 8 8 2.74 +#> 9 9 -0.538 +#> 10 10 0.269 #> # … with 140 more rows #> #> $dens_tbl #> # A tibble: 150 × 2 #> x y #> <dbl> <dbl> -#> 1 -5.12 0.0000872 -#> 2 -5.02 0.000125 -#> 3 -4.92 0.000176 -#> 4 -4.82 0.000247 -#> 5 -4.72 0.000341 -#> 6 -4.62 0.000467 -#> 7 -4.53 0.000634 -#> 8 -4.43 0.000850 -#> 9 -4.33 0.00113 -#> 10 -4.23 0.00148 +#> 1 -5.19 0.0000593 +#> 2 -5.09 0.0000862 +#> 3 -4.99 0.000124 +#> 4 -4.89 0.000176 +#> 5 -4.79 0.000246 +#> 6 -4.69 0.000342 +#> 7 -4.59 0.000467 +#> 8 -4.50 0.000634 +#> 9 -4.40 0.000849 +#> 10 -4.30 0.00112 #> # … with 140 more rows #> #> $input_data #> $input_data$`rnorm(100, 0, 1)` -#> [1] -0.92488617 0.88878323 -1.05156161 2.82410047 0.81244047 0.03623391 -#> [7] 0.31179774 1.10274949 0.52232635 0.02797207 -1.31558760 -0.08488526 -#> [13] 0.65891224 0.45636188 -0.09839675 0.03410962 -0.24675788 1.34399920 -#> [19] 0.22207679 -1.72556965 -0.45909017 0.11793233 -0.84907589 0.14115786 -#> [25] -1.39249285 -0.91418520 0.19655646 0.60103729 -2.36130537 -1.19206239 -#> [31] 1.61102377 0.30940331 0.68187971 1.10216714 -0.62051860 0.21285108 -#> [37] -1.47165960 -1.65637410 -0.94737206 -1.27882347 1.13353046 -0.13357788 -#> [43] -1.83534254 -0.20267171 0.98907568 -0.35728433 -1.20191095 0.45702515 -#> [49] -1.66654511 -0.29459664 0.65240561 -2.29879303 -1.09715605 1.05174544 -#> [55] -0.39302474 0.70067363 0.47834694 -0.81458621 -1.34328261 -0.35320885 -#> [61] 0.33505188 1.71093389 -0.27419588 -1.80938006 -0.92069965 1.45329888 -#> [67] 0.03363828 0.07486503 -0.16234008 -0.56644185 -1.08083396 -0.56210326 -#> [73] 1.40896558 0.13443725 -0.01864006 -0.81613166 0.04082222 0.22558170 -#> [79] 1.11828160 1.25393824 -1.64783208 -2.49016815 -0.07012348 -0.52334032 -#> [85] 0.56819673 -0.19059808 1.46029334 -0.27404032 1.39581427 -0.31427574 -#> [91] 0.05568073 0.17792907 -0.62794106 1.99934604 -0.59527682 -1.51050313 -#> [97] -0.98391247 -0.68410461 0.96567434 -0.98884898 +#> [1] 0.96809413 0.97558858 -0.40756517 -0.42627731 0.02154029 -0.52432827 +#> [7] -0.38738829 2.74076731 -0.53792547 0.26948111 -1.78445962 2.24643383 +#> [13] 1.26493189 1.96092932 -2.24761918 0.48620879 -0.71810854 -1.19139392 +#> [19] -0.01817287 2.00278483 -0.29155987 1.00840438 -0.52852330 -0.85089705 +#> [25] 0.18483544 1.01974679 -0.54400616 -1.41168242 -0.92258953 0.38635917 +#> [31] 1.11937773 -0.09589270 -0.91748327 -0.28551661 0.76816667 0.40025007 +#> [37] 1.24358782 0.33517668 -0.79719940 -1.52538655 -2.34885399 -2.66862812 +#> [43] 0.30478083 -0.13843533 0.31063402 0.70910967 -1.17595199 -1.01132023 +#> [49] 0.82709604 0.35607416 -0.82869311 -0.52556680 -1.03142826 1.10585064 +#> [55] -1.69785205 -0.18128867 1.15663490 -0.62948412 1.22625460 -0.91422000 +#> [61] 1.00469757 0.25999837 0.10996788 0.55913594 -0.44279002 -0.62840048 +#> [67] 1.29919460 -1.31171358 1.73737987 -1.60940430 -1.14286312 -0.38374451 +#> [73] -1.25307756 1.63239469 1.09094332 0.89947466 -0.04712680 -0.59406743 +#> [79] 1.33382486 0.11651601 -1.39706319 -0.73787351 -2.06394902 2.48544615 +#> [85] 1.17771297 -0.67854860 -0.69573897 0.82927667 1.52600077 0.24569111 +#> [91] -1.46739032 0.67374103 0.61598918 0.68089456 -0.65829236 -0.37123276 +#> [97] -0.81860245 1.11463102 -0.07881766 -1.16943995 #> #> $input_data$`tidy_normal(.mean = 5, .sd = 1)` #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 1 5.28 2.11 0.000445 0.609 5.28 -#> 2 1 2 5.27 2.23 0.00130 0.606 5.27 -#> 3 1 3 5.02 2.35 0.00331 0.506 5.02 -#> 4 1 4 4.54 2.47 0.00740 0.324 4.54 -#> 5 1 5 6.20 2.59 0.0146 0.886 6.20 -#> 6 1 6 6.71 2.71 0.0255 0.956 6.71 -#> 7 1 7 5.68 2.82 0.0398 0.751 5.68 -#> 8 1 8 5.68 2.94 0.0561 0.751 5.68 -#> 9 1 9 4.77 3.06 0.0726 0.409 4.77 -#> 10 1 10 4.85 3.18 0.0879 0.442 4.85 +#> 1 1 1 4.90 1.11 0.000243 0.462 4.90 +#> 2 1 2 7.09 1.25 0.000728 0.982 7.09 +#> 3 1 3 4.37 1.40 0.00187 0.265 4.37 +#> 4 1 4 4.58 1.54 0.00412 0.337 4.58 +#> 5 1 5 5.32 1.69 0.00781 0.627 5.32 +#> 6 1 6 4.15 1.83 0.0127 0.199 4.15 +#> 7 1 7 5.61 1.98 0.0180 0.729 5.61 +#> 8 1 8 5.04 2.12 0.0222 0.515 5.04 +#> 9 1 9 5.00 2.26 0.0245 0.502 5.00 +#> 10 1 10 3.95 2.41 0.0251 0.146 3.95 #> # … with 40 more rows #> #> diff --git a/docs/reference/tidy_multi_dist_autoplot-1.png b/docs/reference/tidy_multi_dist_autoplot-1.png index f8882c57..cf4a50ee 100644 Binary files a/docs/reference/tidy_multi_dist_autoplot-1.png and b/docs/reference/tidy_multi_dist_autoplot-1.png differ diff --git a/docs/reference/tidy_multi_dist_autoplot-2.png b/docs/reference/tidy_multi_dist_autoplot-2.png index 7ab0358d..0b0bba4b 100644 Binary files a/docs/reference/tidy_multi_dist_autoplot-2.png and b/docs/reference/tidy_multi_dist_autoplot-2.png differ diff --git a/docs/reference/tidy_multi_single_dist.html b/docs/reference/tidy_multi_single_dist.html index 7e41431d..105767f9 100644 --- a/docs/reference/tidy_multi_single_dist.html +++ b/docs/reference/tidy_multi_single_dist.html @@ -115,16 +115,16 @@

    Examples#> # A tibble: 450 × 8 #> sim_number dist_name x y dx dy p q #> <fct> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 Gaussian c(-1, 1) 1 -1.13 -4.09 0.000446 0.447 -1.13 -#> 2 1 Gaussian c(-1, 1) 2 -1.10 -3.97 0.00128 0.461 -1.10 -#> 3 1 Gaussian c(-1, 1) 3 -1.56 -3.85 0.00321 0.288 -1.56 -#> 4 1 Gaussian c(-1, 1) 4 -0.798 -3.74 0.00709 0.580 -0.798 -#> 5 1 Gaussian c(-1, 1) 5 0.409 -3.62 0.0137 0.921 0.409 -#> 6 1 Gaussian c(-1, 1) 6 -0.156 -3.51 0.0234 0.801 -0.156 -#> 7 1 Gaussian c(-1, 1) 7 -0.894 -3.39 0.0351 0.542 -0.894 -#> 8 1 Gaussian c(-1, 1) 8 -0.512 -3.27 0.0471 0.687 -0.512 -#> 9 1 Gaussian c(-1, 1) 9 -1.62 -3.16 0.0569 0.267 -1.62 -#> 10 1 Gaussian c(-1, 1) 10 -0.761 -3.04 0.0636 0.595 -0.761 +#> 1 1 Gaussian c(-1, 1) 1 -1.63 -4.37 0.000230 0.264 -1.63 +#> 2 1 Gaussian c(-1, 1) 2 0.348 -4.24 0.000612 0.911 0.348 +#> 3 1 Gaussian c(-1, 1) 3 -1.29 -4.10 0.00145 0.385 -1.29 +#> 4 1 Gaussian c(-1, 1) 4 -0.936 -3.97 0.00303 0.525 -0.936 +#> 5 1 Gaussian c(-1, 1) 5 0.853 -3.83 0.00563 0.968 0.853 +#> 6 1 Gaussian c(-1, 1) 6 0.408 -3.70 0.00929 0.920 0.408 +#> 7 1 Gaussian c(-1, 1) 7 -0.983 -3.56 0.0137 0.507 -0.983 +#> 8 1 Gaussian c(-1, 1) 8 0.254 -3.43 0.0180 0.895 0.254 +#> 9 1 Gaussian c(-1, 1) 9 -1.52 -3.29 0.0213 0.303 -1.52 +#> 10 1 Gaussian c(-1, 1) 10 1.08 -3.16 0.0235 0.981 1.08 #> # … with 440 more rows diff --git a/docs/reference/tidy_negative_binomial.html b/docs/reference/tidy_negative_binomial.html index 56fa7f8e..70cca21b 100644 --- a/docs/reference/tidy_negative_binomial.html +++ b/docs/reference/tidy_negative_binomial.html @@ -166,16 +166,16 @@

    Examples#> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> <fct> <int> <int> <dbl> <dbl> <dbl> <dbl> -#> 1 1 1 2 -8.98 0.000135 0.1 0 -#> 2 1 2 20 -7.96 0.000388 0.1 9 -#> 3 1 3 0 -6.94 0.00100 0.1 0 -#> 4 1 4 4 -5.92 0.00233 0.1 1 -#> 5 1 5 4 -4.90 0.00490 0.1 1 -#> 6 1 6 2 -3.89 0.00931 0.1 0 -#> 7 1 7 4 -2.87 0.0161 0.1 1 -#> 8 1 8 5 -1.85 0.0252 0.1 1 -#> 9 1 9 1 -0.826 0.0361 0.1 0 -#> 10 1 10 22 0.194 0.0473 0.1 11 +#> 1 1 1 3 -8.29 0.000208 0.1 1 +#> 2 1 2 0 -7.42 0.000529 0.1 0 +#> 3 1 3 5 -6.55 0.00123 0.1 2 +#> 4 1 4 10 -5.69 0.00260 0.1 4 +#> 5 1 5 12 -4.82 0.00506 0.1 5 +#> 6 1 6 10 -3.95 0.00903 0.1 4 +#> 7 1 7 0 -3.08 0.0149 0.1 0 +#> 8 1 8 4 -2.21 0.0226 0.1 1 +#> 9 1 9 11 -1.34 0.0317 0.1 5 +#> 10 1 10 8 -0.471 0.0415 0.1 3 #> # … with 40 more rows diff --git a/docs/reference/tidy_normal.html b/docs/reference/tidy_normal.html index c640afaf..3a9f0469 100644 --- a/docs/reference/tidy_normal.html +++ b/docs/reference/tidy_normal.html @@ -177,18 +177,18 @@

    Author<

    Examples

    tidy_normal()
 #> # A tibble: 50 × 7
-#>    sim_number     x       y    dx       dy      p       q
-#>    <fct>      <int>   <dbl> <dbl>    <dbl>  <dbl>   <dbl>
-#>  1 1              1 -1.08   -3.51 0.000302 0.139  -1.08  
-#>  2 1              2  1.29   -3.37 0.000772 0.902   1.29  
-#>  3 1              3  0.0857 -3.23 0.00181  0.534   0.0857
-#>  4 1              4  1.60   -3.10 0.00387  0.945   1.60  
-#>  5 1              5 -0.585  -2.96 0.00760  0.279  -0.585 
-#>  6 1              6 -1.31   -2.82 0.0137   0.0956 -1.31  
-#>  7 1              7 -0.684  -2.69 0.0229   0.247  -0.684 
-#>  8 1              8 -2.02   -2.55 0.0355   0.0217 -2.02  
-#>  9 1              9  1.50   -2.42 0.0513   0.933   1.50  
-#> 10 1             10  0.128  -2.28 0.0698   0.551   0.128 
+#>    sim_number     x      y    dx       dy      p      q
+#>    <fct>      <int>  <dbl> <dbl>    <dbl>  <dbl>  <dbl>
+#>  1 1              1 -1.07  -3.14 0.000393 0.142  -1.07 
+#>  2 1              2  0.877 -3.00 0.00102  0.810   0.877
+#>  3 1              3  0.511 -2.87 0.00239  0.695   0.511
+#>  4 1              4 -1.51  -2.73 0.00515  0.0661 -1.51 
+#>  5 1              5 -1.07  -2.60 0.0101   0.143  -1.07 
+#>  6 1              6 -0.576 -2.46 0.0183   0.282  -0.576
+#>  7 1              7 -1.78  -2.33 0.0306   0.0377 -1.78 
+#>  8 1              8  1.31  -2.19 0.0476   0.906   1.31 
+#>  9 1              9 -1.66  -2.06 0.0694   0.0485 -1.66 
+#> 10 1             10  0.743 -1.92 0.0957   0.771   0.743
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_paralogistic.html b/docs/reference/tidy_paralogistic.html index 68dda490..f1dc5bde 100644 --- a/docs/reference/tidy_paralogistic.html +++ b/docs/reference/tidy_paralogistic.html @@ -187,18 +187,18 @@

    Author<

    Examples

    tidy_paralogistic()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y     dx      dy      p       q
-#>    <fct>      <int>  <dbl>  <dbl>   <dbl>  <dbl>   <dbl>
-#>  1 1              1 0.0122 -3.06  0.00103 0      0      
-#>  2 1              2 1.83   -2.37  0.00717 0.0200 0.0694 
-#>  3 1              3 2.22   -1.67  0.0320  0.0392 0.0853 
-#>  4 1              4 1.83   -0.969 0.0920  0.0577 0.0692 
-#>  5 1              5 0.580  -0.270 0.173   0.0755 0.0207 
-#>  6 1              6 2.20    0.428 0.217   0.0926 0.0845 
-#>  7 1              7 0.244   1.13  0.197   0.109  0.00834
-#>  8 1              8 0.255   1.82  0.147   0.125  0.00871
-#>  9 1              9 0.115   2.52  0.108   0.140  0.00369
-#> 10 1             10 2.77    3.22  0.0866  0.155  0.109  
+#>    sim_number     x      y     dx       dy      p       q
+#>    <fct>      <int>  <dbl>  <dbl>    <dbl>  <dbl>   <dbl>
+#>  1 1              1 2.75   -1.76  0.000797 0      0.198  
+#>  2 1              2 0.312  -1.35  0.00596  0.0200 0.0181 
+#>  3 1              3 0.899  -0.937 0.0288   0.0392 0.0564 
+#>  4 1              4 0.391  -0.528 0.0920   0.0577 0.0231 
+#>  5 1              5 1.36   -0.119 0.200    0.0755 0.0889 
+#>  6 1              6 0.332   0.290 0.308    0.0926 0.0194 
+#>  7 1              7 0.839   0.699 0.354    0.109  0.0524 
+#>  8 1              8 2.01    1.11  0.321    0.125  0.137  
+#>  9 1              9 0.207   1.52  0.241    0.140  0.0116 
+#> 10 1             10 0.0925  1.93  0.163    0.155  0.00455
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_pareto.html b/docs/reference/tidy_pareto.html index a440cbaa..b64a7c77 100644 --- a/docs/reference/tidy_pareto.html +++ b/docs/reference/tidy_pareto.html @@ -179,18 +179,18 @@

    Author<

    Examples

    tidy_pareto()
 #> # A tibble: 50 × 7
-#>    sim_number     x       y        dx     dy     p          q
-#>    <fct>      <int>   <dbl>     <dbl>  <dbl> <dbl>      <dbl>
-#>  1 1              1 0.00685 -0.0111    0.105 0       0.00133 
-#>  2 1              2 0.0226  -0.00955   0.384 0.844   0.00550 
-#>  3 1              3 0.00811 -0.00799   1.20  0.967   0.00161 
-#>  4 1              4 0.0164  -0.00643   3.21  0.992   0.00364 
-#>  5 1              5 0.0121  -0.00486   7.34  0.997   0.00253 
-#>  6 1              6 0.0178  -0.00330  14.5   0.999   0.00404 
-#>  7 1              7 0.00183 -0.00174  24.6   1.00    0.000318
-#>  8 1              8 0.0542  -0.000177 36.4   1.00  Inf       
-#>  9 1              9 0.0125   0.00139  47.1   1.00    0.00262 
-#> 10 1             10 0.00384  0.00295  54.0   1.00    0.000711
+#>    sim_number     x        y        dx     dy     p         q
+#>    <fct>      <int>    <dbl>     <dbl>  <dbl> <dbl>     <dbl>
+#>  1 1              1 0.00558  -0.00860   0.184 0     0.000443 
+#>  2 1              2 0.000652 -0.00567   2.96  0.844 0.0000405
+#>  3 1              3 0.00357  -0.00275  19.1   0.967 0.000276 
+#>  4 1              4 0.00145   0.000178 52.7   0.992 0.000105 
+#>  5 1              5 0.0183    0.00310  69.8   0.997 0.00157  
+#>  6 1              6 0.00139   0.00603  55.1   0.999 0.0000998
+#>  7 1              7 0.00122   0.00895  34.6   1.00  0.0000863
+#>  8 1              8 0.00169   0.0119   20.1   1.00  0.000124 
+#>  9 1              9 0.00212   0.0148   10.2   1.00  0.000159 
+#> 10 1             10 0.0354    0.0177    6.03  1.00  0.00334  
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_pareto1.html b/docs/reference/tidy_pareto1.html index 55b21318..4f540d28 100644 --- a/docs/reference/tidy_pareto1.html +++ b/docs/reference/tidy_pareto1.html @@ -179,18 +179,18 @@

    Author<

    Examples

    tidy_pareto1()
 #> # A tibble: 50 × 7
-#>    sim_number     x     y     dx      dy     p      q
-#>    <fct>      <int> <dbl>  <dbl>   <dbl> <dbl>  <dbl>
-#>  1 1              1  1.24 -0.801 0.00162     0   1.00
-#>  2 1              2  2.20  0.189 0.0748      0   1.03
-#>  3 1              3  6.35  1.18  0.326       0   1.13
-#>  4 1              4  4.10  2.17  0.259       0   1.07
-#>  5 1              5 45.9   3.16  0.131       0 Inf   
-#>  6 1              6  2.17  4.15  0.0510      0   1.03
-#>  7 1              7  2.83  5.14  0.00977     0   1.04
-#>  8 1              8  2.72  6.13  0.0366      0   1.04
-#>  9 1              9  1.11  7.12  0.0384      0   1.00
-#> 10 1             10  2.14  8.11  0.0229      0   1.03
+#>    sim_number     x     y     dx       dy     p     q
+#>    <fct>      <int> <dbl>  <dbl>    <dbl> <dbl> <dbl>
+#>  1 1              1  2.33 -2.18  0.000648     0  1.03
+#>  2 1              2  1.65 -1.23  0.00800      0  1.02
+#>  3 1              3 12.5  -0.278 0.0476       0  1.40
+#>  4 1              4 37.3   0.672 0.141        0 10.3 
+#>  5 1              5  1.48  1.62  0.216        0  1.01
+#>  6 1              6  1.24  2.57  0.189        0  1.01
+#>  7 1              7  2.38  3.52  0.111        0  1.04
+#>  8 1              8  4.36  4.48  0.0629       0  1.09
+#>  9 1              9  1.91  5.43  0.0423       0  1.02
+#> 10 1             10  3.28  6.38  0.0279       0  1.06
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_poisson.html b/docs/reference/tidy_poisson.html index 23d8eab2..18820793 100644 --- a/docs/reference/tidy_poisson.html +++ b/docs/reference/tidy_poisson.html @@ -158,16 +158,16 @@

    Examples#> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> <fct> <int> <int> <dbl> <dbl> <dbl> <dbl> -#> 1 1 1 0 -1.32 0.00449 0.368 0 -#> 2 1 2 1 -1.18 0.0108 0.368 0 -#> 3 1 3 2 -1.05 0.0235 0.368 1 -#> 4 1 4 1 -0.913 0.0466 0.368 0 -#> 5 1 5 1 -0.777 0.0841 0.368 0 -#> 6 1 6 0 -0.642 0.138 0.368 0 -#> 7 1 7 0 -0.506 0.207 0.368 0 -#> 8 1 8 0 -0.371 0.282 0.368 0 -#> 9 1 9 0 -0.235 0.351 0.368 0 -#> 10 1 10 0 -0.0998 0.400 0.368 0 +#> 1 1 1 5 -0.921 0.00322 0.368 Inf +#> 2 1 2 0 -0.782 0.0113 0.368 0 +#> 3 1 3 1 -0.642 0.0323 0.368 0 +#> 4 1 4 2 -0.502 0.0752 0.368 1 +#> 5 1 5 1 -0.363 0.142 0.368 0 +#> 6 1 6 2 -0.223 0.220 0.368 1 +#> 7 1 7 1 -0.0835 0.276 0.368 0 +#> 8 1 8 3 0.0561 0.286 0.368 1 +#> 9 1 9 1 0.196 0.253 0.368 0 +#> 10 1 10 0 0.335 0.215 0.368 0 #> # … with 40 more rows diff --git a/docs/reference/tidy_random_walk.html b/docs/reference/tidy_random_walk.html index 8b0459cd..ba70dc89 100644 --- a/docs/reference/tidy_random_walk.html +++ b/docs/reference/tidy_random_walk.html @@ -133,18 +133,18 @@

    Examples
    tidy_normal(.sd = .1, .num_sims = 25) %>%
   tidy_random_walk()
 #> # A tibble: 1,250 × 8
-#>    sim_number     x         y     dx      dy     p         q random_walk_value
-#>    <fct>      <int>     <dbl>  <dbl>   <dbl> <dbl>     <dbl>             <dbl>
-#>  1 1              1 -0.125    -0.307 0.00328 0.105 -0.125              -0.125 
-#>  2 1              2 -0.0905   -0.292 0.0125  0.183 -0.0905             -0.204 
-#>  3 1              3  0.161    -0.276 0.0391  0.946  0.161              -0.0764
-#>  4 1              4  0.0463   -0.260 0.101   0.678  0.0463             -0.0336
-#>  5 1              5  0.0521   -0.244 0.215   0.699  0.0521              0.0167
-#>  6 1              6 -0.0336   -0.228 0.384   0.369 -0.0336             -0.0174
-#>  7 1              7  0.210    -0.212 0.578   0.982  0.210               0.189 
-#>  8 1              8 -0.000324 -0.196 0.753   0.499 -0.000324            0.189 
-#>  9 1              9 -0.0361   -0.180 0.878   0.359 -0.0361              0.146 
-#> 10 1             10 -0.0597   -0.165 0.969   0.275 -0.0597              0.0776
+#>    sim_number     x         y     dx      dy       p         q random_walk_value
+#>    <fct>      <int>     <dbl>  <dbl>   <dbl>   <dbl>     <dbl>             <dbl>
+#>  1 1              1  0.000858 -0.425 0.00209 0.503    0.000858          0.000858
+#>  2 1              2 -0.0531   -0.409 0.00619 0.298   -0.0531           -0.0523  
+#>  3 1              3  0.0424   -0.392 0.0158  0.664    0.0424           -0.0121  
+#>  4 1              4 -0.296    -0.375 0.0348  0.00153 -0.296            -0.305   
+#>  5 1              5 -0.0388   -0.358 0.0657  0.349   -0.0388           -0.332   
+#>  6 1              6  0.00923  -0.342 0.107   0.537    0.00923          -0.326   
+#>  7 1              7 -0.0132   -0.325 0.150   0.448   -0.0132           -0.334   
+#>  8 1              8  0.0568   -0.308 0.184   0.715    0.0568           -0.297   
+#>  9 1              9  0.155    -0.291 0.197   0.939    0.155            -0.188   
+#> 10 1             10  0.0659   -0.275 0.194   0.745    0.0659           -0.134   
 #> # … with 1,240 more rows
    diff --git a/docs/reference/tidy_random_walk_autoplot-1.png b/docs/reference/tidy_random_walk_autoplot-1.png index b6417dd3..852f2f5c 100644 Binary files a/docs/reference/tidy_random_walk_autoplot-1.png and b/docs/reference/tidy_random_walk_autoplot-1.png differ diff --git a/docs/reference/tidy_random_walk_autoplot-2.png b/docs/reference/tidy_random_walk_autoplot-2.png index e3a9bd83..8f6b8237 100644 Binary files a/docs/reference/tidy_random_walk_autoplot-2.png and b/docs/reference/tidy_random_walk_autoplot-2.png differ diff --git a/docs/reference/tidy_scale_zero_one_vec-1.png b/docs/reference/tidy_scale_zero_one_vec-1.png index 3156dad5..e851e686 100644 Binary files a/docs/reference/tidy_scale_zero_one_vec-1.png and b/docs/reference/tidy_scale_zero_one_vec-1.png differ diff --git a/docs/reference/tidy_skewness_vec.html b/docs/reference/tidy_skewness_vec.html index 30098b7c..ea0bcffd 100644 --- a/docs/reference/tidy_skewness_vec.html +++ b/docs/reference/tidy_skewness_vec.html @@ -119,7 +119,7 @@

    Author<

    Examples

    tidy_skewness_vec(rnorm(100, 3, 2))
-#> [1] -0.0406822
+#> [1] -0.1636212
    diff --git a/docs/reference/tidy_stat_tbl.html b/docs/reference/tidy_stat_tbl.html index 0e47ace6..8b01e268 100644 --- a/docs/reference/tidy_stat_tbl.html +++ b/docs/reference/tidy_stat_tbl.html @@ -155,62 +155,62 @@

    Examples tidy_stat_tbl(tn, y, quantile, "vector", probs = p, na.rm = TRUE) #> sim_number_1 sim_number_2 sim_number_3 -#> 2.5% -2.06271343 -1.6858257 -1.8377483 -#> 25% -0.89231070 -0.6371119 -0.9081756 -#> 50% -0.05390428 -0.1477999 0.0264237 -#> 75% 0.57906055 0.5406522 0.6626329 -#> 95% 1.63141412 1.4790906 1.2962458 +#> 2.5% -1.9639261 -2.16592793 -1.931909521 +#> 25% -0.7872943 -0.40661213 -0.737074285 +#> 50% -0.1080782 -0.06406365 0.001169794 +#> 75% 0.6202621 0.50109523 0.716021156 +#> 95% 1.4635127 1.30349404 1.730100061 tidy_stat_tbl(tn, y, quantile, "list", probs = p) #> $sim_number_1 -#> 2.5% 25% 50% 75% 95% -#> -2.06271343 -0.89231070 -0.05390428 0.57906055 1.63141412 +#> 2.5% 25% 50% 75% 95% +#> -1.9639261 -0.7872943 -0.1080782 0.6202621 1.4635127 #> #> $sim_number_2 -#> 2.5% 25% 50% 75% 95% -#> -1.6858257 -0.6371119 -0.1477999 0.5406522 1.4790906 +#> 2.5% 25% 50% 75% 95% +#> -2.16592793 -0.40661213 -0.06406365 0.50109523 1.30349404 #> #> $sim_number_3 -#> 2.5% 25% 50% 75% 95% -#> -1.8377483 -0.9081756 0.0264237 0.6626329 1.2962458 +#> 2.5% 25% 50% 75% 95% +#> -1.931909521 -0.737074285 0.001169794 0.716021156 1.730100061 #> tidy_stat_tbl(tn, y, quantile, "tibble", probs = p) #> # A tibble: 15 × 3 #> sim_number name quantile #> <fct> <chr> <dbl> -#> 1 1 2.5% -2.06 -#> 2 1 25% -0.892 -#> 3 1 50% -0.0539 -#> 4 1 75% 0.579 -#> 5 1 95% 1.63 -#> 6 2 2.5% -1.69 -#> 7 2 25% -0.637 -#> 8 2 50% -0.148 -#> 9 2 75% 0.541 -#> 10 2 95% 1.48 -#> 11 3 2.5% -1.84 -#> 12 3 25% -0.908 -#> 13 3 50% 0.0264 -#> 14 3 75% 0.663 -#> 15 3 95% 1.30 +#> 1 1 2.5% -1.96 +#> 2 1 25% -0.787 +#> 3 1 50% -0.108 +#> 4 1 75% 0.620 +#> 5 1 95% 1.46 +#> 6 2 2.5% -2.17 +#> 7 2 25% -0.407 +#> 8 2 50% -0.0641 +#> 9 2 75% 0.501 +#> 10 2 95% 1.30 +#> 11 3 2.5% -1.93 +#> 12 3 25% -0.737 +#> 13 3 50% 0.00117 +#> 14 3 75% 0.716 +#> 15 3 95% 1.73 tidy_stat_tbl(tn, y, quantile, .use_data_table = TRUE, probs = p, na.rm = TRUE) #> # A tibble: 15 × 3 #> sim_number name quantile #> <fct> <fct> <dbl> -#> 1 1 2.5% -2.06 -#> 2 1 25% -0.892 -#> 3 1 50% -0.0539 -#> 4 1 75% 0.579 -#> 5 1 95% 1.63 -#> 6 2 2.5% -1.69 -#> 7 2 25% -0.637 -#> 8 2 50% -0.148 -#> 9 2 75% 0.541 -#> 10 2 95% 1.48 -#> 11 3 2.5% -1.84 -#> 12 3 25% -0.908 -#> 13 3 50% 0.0264 -#> 14 3 75% 0.663 -#> 15 3 95% 1.30 +#> 1 1 2.5% -1.96 +#> 2 1 25% -0.787 +#> 3 1 50% -0.108 +#> 4 1 75% 0.620 +#> 5 1 95% 1.46 +#> 6 2 2.5% -2.17 +#> 7 2 25% -0.407 +#> 8 2 50% -0.0641 +#> 9 2 75% 0.501 +#> 10 2 95% 1.30 +#> 11 3 2.5% -1.93 +#> 12 3 25% -0.737 +#> 13 3 50% 0.00117 +#> 14 3 75% 0.716 +#> 15 3 95% 1.73 diff --git a/docs/reference/tidy_t.html b/docs/reference/tidy_t.html index 4cb8f43d..814c5343 100644 --- a/docs/reference/tidy_t.html +++ b/docs/reference/tidy_t.html @@ -175,18 +175,18 @@

    Author<

    Examples

    tidy_t()
 #> # A tibble: 50 × 7
-#>    sim_number     x        y    dx       dy     p       q
-#>    <fct>      <int>    <dbl> <dbl>    <dbl> <dbl>   <dbl>
-#>  1 1              1   0.0320 -64.5 2.25e- 4 0.5      3.56
-#>  2 1              2  -0.338  -63.1 1.67e- 2 0.506    3.35
-#>  3 1              3  -0.204  -61.6 7.37e- 5 0.513    3.42
-#>  4 1              4  -4.35   -60.1 1.54e-11 0.519    1.96
-#>  5 1              5 -63.1    -58.7 4.81e-18 0.526 -Inf   
-#>  6 1              6   2.23   -57.2 2.38e-18 0.532    5.69
-#>  7 1              7  -0.934  -55.7 6.37e-19 0.539    3.04
-#>  8 1              8  -2.00   -54.2 0        0.545    2.61
-#>  9 1              9  -0.0224 -52.8 0        0.552    3.53
-#> 10 1             10  -0.910  -51.3 2.92e-19 0.558    3.06
+#>    sim_number     x      y     dx       dy     p      q
+#>    <fct>      <int>  <dbl>  <dbl>    <dbl> <dbl>  <dbl>
+#>  1 1              1 -0.462 -26.8  2.15e- 4 0.5   -1.25 
+#>  2 1              2 -0.340 -24.4  3.58e- 3 0.506 -1.24 
+#>  3 1              3  0.105 -21.9  3.96e- 4 0.513 -1.21 
+#>  4 1              4 -0.616 -19.5  2.95e-15 0.519 -1.26 
+#>  5 1              5 -0.414 -17.1  0        0.526 -1.25 
+#>  6 1              6  4.02  -14.7  0        0.532 -0.979
+#>  7 1              7  5.83  -12.2  1.69e-12 0.539 -0.888
+#>  8 1              8  0.371  -9.81 2.51e- 3 0.545 -1.19 
+#>  9 1              9 -0.134  -7.38 8.53e- 3 0.552 -1.23 
+#> 10 1             10  0.141  -4.96 7.12e- 3 0.558 -1.21 
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_uniform.html b/docs/reference/tidy_uniform.html index 96f2044b..1fb985a1 100644 --- a/docs/reference/tidy_uniform.html +++ b/docs/reference/tidy_uniform.html @@ -178,16 +178,16 @@

    Examples#> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 1 0.427 -0.352 0.00184 0 0.428 -#> 2 1 2 0.776 -0.317 0.00450 0.0204 0.792 -#> 3 1 3 0.972 -0.282 0.0102 0.0408 0.996 -#> 4 1 4 0.520 -0.248 0.0218 0.0612 0.525 -#> 5 1 5 0.877 -0.213 0.0431 0.0816 0.897 -#> 6 1 6 0.253 -0.179 0.0800 0.102 0.246 -#> 7 1 7 0.976 -0.144 0.139 0.122 1 -#> 8 1 8 0.626 -0.109 0.226 0.143 0.635 -#> 9 1 9 0.616 -0.0747 0.344 0.163 0.625 -#> 10 1 10 0.397 -0.0401 0.492 0.184 0.396 +#> 1 1 1 0.170 -0.319 0.00234 0 0.126 +#> 2 1 2 0.682 -0.284 0.00553 0.0204 0.672 +#> 3 1 3 0.417 -0.250 0.0121 0.0408 0.389 +#> 4 1 4 0.864 -0.216 0.0249 0.0612 0.865 +#> 5 1 5 0.765 -0.182 0.0476 0.0816 0.760 +#> 6 1 6 0.222 -0.147 0.0852 0.102 0.181 +#> 7 1 7 0.756 -0.113 0.143 0.122 0.750 +#> 8 1 8 0.232 -0.0788 0.224 0.143 0.192 +#> 9 1 9 0.931 -0.0445 0.330 0.163 0.936 +#> 10 1 10 0.220 -0.0102 0.457 0.184 0.179 #> # … with 40 more rows diff --git a/docs/reference/tidy_weibull.html b/docs/reference/tidy_weibull.html index 25dbde38..92a7cb86 100644 --- a/docs/reference/tidy_weibull.html +++ b/docs/reference/tidy_weibull.html @@ -177,18 +177,18 @@

    Author<

    Examples

    tidy_weibull()
 #> # A tibble: 50 × 7
-#>    sim_number     x      y      dx      dy      p       q
-#>    <fct>      <int>  <dbl>   <dbl>   <dbl>  <dbl>   <dbl>
-#>  1 1              1 0.316  -1.20   0.00166 0      0.0833 
-#>  2 1              2 0.715  -1.07   0.00443 0.0202 0.200  
-#>  3 1              3 0.429  -0.939  0.0107  0.0400 0.115  
-#>  4 1              4 0.618  -0.810  0.0237  0.0594 0.170  
-#>  5 1              5 0.386  -0.681  0.0476  0.0784 0.103  
-#>  6 1              6 2.29   -0.551  0.0871  0.0970 0.874  
-#>  7 1              7 1.76   -0.422  0.146   0.115  0.594  
-#>  8 1              8 0.340  -0.293  0.225   0.133  0.0898 
-#>  9 1              9 0.0320 -0.164  0.318   0.151  0.00761
-#> 10 1             10 0.191  -0.0346 0.414   0.168  0.0493 
+#>    sim_number     x      y      dx      dy      p      q
+#>    <fct>      <int>  <dbl>   <dbl>   <dbl>  <dbl>  <dbl>
+#>  1 1              1 0.172  -0.889  0.00129 0      0.0358
+#>  2 1              2 0.895  -0.786  0.00352 0.0202 0.311 
+#>  3 1              3 0.839  -0.684  0.00874 0.0400 0.286 
+#>  4 1              4 0.188  -0.582  0.0197  0.0594 0.0411
+#>  5 1              5 2.53   -0.479  0.0402  0.0784 1.57  
+#>  6 1              6 0.715  -0.377  0.0746  0.0970 0.235 
+#>  7 1              7 0.679  -0.274  0.126   0.115  0.220 
+#>  8 1              8 0.0619 -0.172  0.195   0.133  0     
+#>  9 1              9 0.515  -0.0691 0.277   0.151  0.157 
+#> 10 1             10 0.442   0.0334 0.362   0.168  0.130 
 #> # … with 40 more rows
    diff --git a/docs/reference/tidy_zero_truncated_poisson.html b/docs/reference/tidy_zero_truncated_poisson.html index ccf82dc5..d88dfeb2 100644 --- a/docs/reference/tidy_zero_truncated_poisson.html +++ b/docs/reference/tidy_zero_truncated_poisson.html @@ -160,16 +160,16 @@

    Examples#> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> <fct> <int> <int> <dbl> <dbl> <dbl> <dbl> -#> 1 1 1 2 0.0786 0.00847 0 1 -#> 2 1 2 3 0.157 0.0176 0 Inf -#> 3 1 3 1 0.235 0.0343 0 1 -#> 4 1 4 2 0.314 0.0625 0 1 -#> 5 1 5 1 0.392 0.107 0 1 -#> 6 1 6 1 0.471 0.171 0 1 -#> 7 1 7 2 0.549 0.257 0 1 -#> 8 1 8 1 0.628 0.362 0 1 -#> 9 1 9 1 0.706 0.477 0 1 -#> 10 1 10 3 0.784 0.589 0 Inf +#> 1 1 1 1 0.0786 0.00992 0 1 +#> 2 1 2 1 0.177 0.0247 0 1 +#> 3 1 3 2 0.276 0.0554 0 1 +#> 4 1 4 1 0.375 0.112 0 1 +#> 5 1 5 1 0.474 0.204 0 1 +#> 6 1 6 1 0.573 0.336 0 1 +#> 7 1 7 2 0.672 0.499 0 1 +#> 8 1 8 1 0.770 0.668 0 1 +#> 9 1 9 1 0.869 0.807 0 1 +#> 10 1 10 1 0.968 0.879 0 1 #> # … with 40 more rows diff --git a/docs/reference/util_bernoulli_param_estimate-1.png b/docs/reference/util_bernoulli_param_estimate-1.png index 5eca00f6..d61cee95 100644 Binary files a/docs/reference/util_bernoulli_param_estimate-1.png and b/docs/reference/util_bernoulli_param_estimate-1.png differ diff --git a/docs/reference/util_bernoulli_param_estimate.html b/docs/reference/util_bernoulli_param_estimate.html index 10b59f74..207a32f2 100644 --- a/docs/reference/util_bernoulli_param_estimate.html +++ b/docs/reference/util_bernoulli_param_estimate.html @@ -139,7 +139,7 @@

    Examples#> # A tibble: 1 × 8 #> dist_type samp_size min max mean variance sum_x prob #> <chr> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 Bernoulli 50 0 1 0.02 0.0196 1 0.02 +#> 1 Bernoulli 50 0 1 0.06 0.0564 3 0.06 output$combined_data_tbl %>% tidy_combined_autoplot() diff --git a/docs/reference/util_bernoulli_stats_tbl.html b/docs/reference/util_bernoulli_stats_tbl.html index 40cd29f6..6408ead7 100644 --- a/docs/reference/util_bernoulli_stats_tbl.html +++ b/docs/reference/util_bernoulli_stats_tbl.html @@ -134,10 +134,10 @@

    Examples#> $ mad <dbl> 0.5 #> $ entropy <dbl> 0.325083 #> $ fisher_information <dbl> 11.11111 -#> $ computed_std_skew <dbl> 4.694855 -#> $ computed_std_kurt <dbl> 23.04167 +#> $ computed_std_skew <dbl> 3.096281 +#> $ computed_std_kurt <dbl> 10.58696 #> $ ci_lo <dbl> 0 -#> $ ci_hi <dbl> 0.775 +#> $ ci_hi <dbl> 1 diff --git a/docs/reference/util_beta_param_estimate-1.png b/docs/reference/util_beta_param_estimate-1.png index fddea187..7ea967f0 100644 Binary files a/docs/reference/util_beta_param_estimate-1.png and b/docs/reference/util_beta_param_estimate-1.png differ diff --git a/docs/reference/util_beta_param_estimate.html b/docs/reference/util_beta_param_estimate.html index 8e4f6346..025cfe4f 100644 --- a/docs/reference/util_beta_param_estimate.html +++ b/docs/reference/util_beta_param_estimate.html @@ -178,9 +178,9 @@

    Examples#> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape1 shape2 shape…¹ #> <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Beta 50 0.101 0.971 0.623 0.0441 Bayes 31.2 18.8 1.66 -#> 2 Beta 50 0.101 0.971 0.623 0.0441 NIST_MME 2.70 1.63 1.66 -#> 3 Beta 50 0.101 0.971 0.623 0.0441 EnvStats… 2.76 1.67 1.66 +#> 1 Beta 50 0.196 0.989 0.629 0.0350 Bayes 31.4 18.6 1.69 +#> 2 Beta 50 0.196 0.989 0.629 0.0350 NIST_MME 3.57 2.11 1.69 +#> 3 Beta 50 0.196 0.989 0.629 0.0350 EnvStats… 3.65 2.16 1.69 #> # … with abbreviated variable name ¹​shape_ratio diff --git a/docs/reference/util_beta_stats_tbl.html b/docs/reference/util_beta_stats_tbl.html index 752869f3..d3fff549 100644 --- a/docs/reference/util_beta_stats_tbl.html +++ b/docs/reference/util_beta_stats_tbl.html @@ -134,10 +134,10 @@

    Examples#> $ coeff_var <dbl> 0.5773503 #> $ skewness <dbl> 0 #> $ kurtosis <lgl> NA -#> $ computed_std_skew <dbl> -0.4044672 -#> $ computed_std_kurt <dbl> 2.234254 -#> $ ci_lo <dbl> 0.02580016 -#> $ ci_hi <dbl> 0.9298892 +#> $ computed_std_skew <dbl> 0.06575886 +#> $ computed_std_kurt <dbl> 1.756644 +#> $ ci_lo <dbl> 0.06993433 +#> $ ci_hi <dbl> 0.9717098 diff --git a/docs/reference/util_binomial_param_estimate-1.png b/docs/reference/util_binomial_param_estimate-1.png index 08cb8d33..f08ed540 100644 Binary files a/docs/reference/util_binomial_param_estimate-1.png and b/docs/reference/util_binomial_param_estimate-1.png differ diff --git a/docs/reference/util_cauchy_param_estimate-1.png b/docs/reference/util_cauchy_param_estimate-1.png index df6af6ea..d0930115 100644 Binary files a/docs/reference/util_cauchy_param_estimate-1.png and b/docs/reference/util_cauchy_param_estimate-1.png differ diff --git a/docs/reference/util_cauchy_param_estimate.html b/docs/reference/util_cauchy_param_estimate.html index a4782fae..3e7d687f 100644 --- a/docs/reference/util_cauchy_param_estimate.html +++ b/docs/reference/util_cauchy_param_estimate.html @@ -133,9 +133,9 @@

    Examples output$parameter_tbl #> # A tibble: 1 × 8 -#> dist_type samp_size min max method location scale ratio -#> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Cauchy 50 -98.3 20.2 MASS 0.0754 1.59 0.0473 +#> dist_type samp_size min max method location scale ratio +#> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> +#> 1 Cauchy 50 -119. 40.6 MASS -0.0599 2.01 -0.0298 output$combined_data_tbl %>% tidy_combined_autoplot() diff --git a/docs/reference/util_cauchy_stats_tbl.html b/docs/reference/util_cauchy_stats_tbl.html index c5b7c4f8..920c312a 100644 --- a/docs/reference/util_cauchy_stats_tbl.html +++ b/docs/reference/util_cauchy_stats_tbl.html @@ -133,10 +133,10 @@

    Examples#> $ coeff_var <chr> "undefined" #> $ skewness <dbl> 0 #> $ kurtosis <chr> "undefined" -#> $ computed_std_skew <dbl> 2.338888 -#> $ computed_std_kurt <dbl> 16.64017 -#> $ ci_lo <dbl> -6.451524 -#> $ ci_hi <dbl> 8.968239 +#> $ computed_std_skew <dbl> 3.338946 +#> $ computed_std_kurt <dbl> 16.69811 +#> $ ci_lo <dbl> -3.869178 +#> $ ci_hi <dbl> 13.64284 diff --git a/docs/reference/util_chisquare_stats_tbl.html b/docs/reference/util_chisquare_stats_tbl.html index 3b5e6a9b..b749a1a7 100644 --- a/docs/reference/util_chisquare_stats_tbl.html +++ b/docs/reference/util_chisquare_stats_tbl.html @@ -132,10 +132,10 @@

    Examples#> $ coeff_var <dbl> 1.414214 #> $ skewness <dbl> 2.828427 #> $ kurtosis <dbl> 15 -#> $ computed_std_skew <dbl> 1.80429 -#> $ computed_std_kurt <dbl> 6.598183 -#> $ ci_lo <dbl> 0.009104106 -#> $ ci_hi <dbl> 7.089998 +#> $ computed_std_skew <dbl> 0.9979738 +#> $ computed_std_kurt <dbl> 2.820907 +#> $ ci_lo <dbl> 0.009561891 +#> $ ci_hi <dbl> 7.009665 diff --git a/docs/reference/util_exponential_param_estimate-1.png b/docs/reference/util_exponential_param_estimate-1.png index 5c1b6a4e..41bcf99b 100644 Binary files a/docs/reference/util_exponential_param_estimate-1.png and b/docs/reference/util_exponential_param_estimate-1.png differ diff --git a/docs/reference/util_exponential_param_estimate.html b/docs/reference/util_exponential_param_estimate.html index 9f834925..35b54006 100644 --- a/docs/reference/util_exponential_param_estimate.html +++ b/docs/reference/util_exponential_param_estimate.html @@ -138,7 +138,7 @@

    Examples#> # A tibble: 1 × 8 #> dist_type samp_size min max mean variance method rate #> <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> -#> 1 Exponential 50 0.240 40.7 11.5 121. NIST_MME 0.0870 +#> 1 Exponential 50 0.112 42.8 12.4 120. NIST_MME 0.0805 output$combined_data_tbl %>% tidy_combined_autoplot() diff --git a/docs/reference/util_exponential_stats_tbl.html b/docs/reference/util_exponential_stats_tbl.html index d95c8c9d..f637b4ed 100644 --- a/docs/reference/util_exponential_stats_tbl.html +++ b/docs/reference/util_exponential_stats_tbl.html @@ -135,10 +135,10 @@

    Examples#> $ coeff_var <dbl> 1 #> $ skewness <dbl> 2 #> $ kurtosis <dbl> 9 -#> $ computed_std_skew <dbl> 3.194111 -#> $ computed_std_kurt <dbl> 16.7398 -#> $ ci_lo <dbl> 0.0273818 -#> $ ci_hi <dbl> 2.733512 +#> $ computed_std_skew <dbl> 1.018969 +#> $ computed_std_kurt <dbl> 3.549073 +#> $ ci_lo <dbl> 0.04006036 +#> $ ci_hi <dbl> 2.808457 diff --git a/docs/reference/util_f_stats_tbl.html b/docs/reference/util_f_stats_tbl.html index 93f79db1..c9c99702 100644 --- a/docs/reference/util_f_stats_tbl.html +++ b/docs/reference/util_f_stats_tbl.html @@ -121,7 +121,7 @@

    Examples#> Columns: 17 #> $ tidy_function <chr> "tidy_f" #> $ function_call <chr> "F Distribution c(1, 1, 0)" -#> $ distribution <chr> "F" +#> $ distribution <chr> "f" #> $ distribution_type <chr> "continuous" #> $ points <dbl> 50 #> $ simulations <dbl> 1 @@ -132,10 +132,10 @@

    Examples#> $ coeff_var <chr> "undefined" #> $ skewness <chr> "undefined" #> $ kurtosis <chr> "Not computed" -#> $ computed_std_skew <dbl> 6.821724 -#> $ computed_std_kurt <dbl> 47.69216 -#> $ ci_lo <dbl> 0.006746585 -#> $ ci_hi <dbl> 97.10469 +#> $ computed_std_skew <dbl> 6.799377 +#> $ computed_std_kurt <dbl> 47.48836 +#> $ ci_lo <dbl> 0.01065216 +#> $ ci_hi <dbl> 66.38577 diff --git a/docs/reference/util_gamma_param_estimate-1.png b/docs/reference/util_gamma_param_estimate-1.png index a812c15d..589de518 100644 Binary files a/docs/reference/util_gamma_param_estimate-1.png and b/docs/reference/util_gamma_param_estimate-1.png differ diff --git a/docs/reference/util_gamma_param_estimate.html b/docs/reference/util_gamma_param_estimate.html index b9ba99f5..01e9b902 100644 --- a/docs/reference/util_gamma_param_estimate.html +++ b/docs/reference/util_gamma_param_estimate.html @@ -138,9 +138,9 @@

    Examples#> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape scale shape…¹ #> <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Gamma 50 0.00810 0.896 0.275 0.233 NIST_MME 1.39 0.198 7.03 -#> 2 Gamma 50 0.00810 0.896 0.275 0.233 EnvStats… 1.36 0.198 6.89 -#> 3 Gamma 50 0.00810 0.896 0.275 0.233 EnvStats… 1.32 0.198 6.68 +#> 1 Gamma 50 0.00231 1.04 0.295 0.279 NIST_MME 1.11 0.264 4.22 +#> 2 Gamma 50 0.00231 1.04 0.295 0.279 EnvStats… 1.09 0.264 4.13 +#> 3 Gamma 50 0.00231 1.04 0.295 0.279 EnvStats… 1.06 0.264 4.01 #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% diff --git a/docs/reference/util_gamma_stats_tbl.html b/docs/reference/util_gamma_stats_tbl.html index 69b1f420..b890a770 100644 --- a/docs/reference/util_gamma_stats_tbl.html +++ b/docs/reference/util_gamma_stats_tbl.html @@ -134,10 +134,10 @@

    Examples#> $ coeff_var <dbl> 1 #> $ skewness <dbl> 2 #> $ kurtosis <dbl> 9 -#> $ computed_std_skew <dbl> 1.997294 -#> $ computed_std_kurt <dbl> 7.785293 -#> $ ci_lo <dbl> 0.01357778 -#> $ ci_hi <dbl> 0.805893 +#> $ computed_std_skew <dbl> 1.104969 +#> $ computed_std_kurt <dbl> 3.450766 +#> $ ci_lo <dbl> 0.004632404 +#> $ ci_hi <dbl> 0.8097946 diff --git a/docs/reference/util_geometric_param_estimate-1.png b/docs/reference/util_geometric_param_estimate-1.png index be08ffd9..b4284238 100644 Binary files a/docs/reference/util_geometric_param_estimate-1.png and b/docs/reference/util_geometric_param_estimate-1.png differ diff --git a/docs/reference/util_geometric_param_estimate.html b/docs/reference/util_geometric_param_estimate.html index c664869f..35adb795 100644 --- a/docs/reference/util_geometric_param_estimate.html +++ b/docs/reference/util_geometric_param_estimate.html @@ -140,8 +140,8 @@

    Examples#> # A tibble: 2 × 9 #> dist_type samp_size min max mean variance sum_x method shape #> <chr> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> -#> 1 Geometric 50 0 39 9.32 65.7 466 EnvStats_MME 0.0969 -#> 2 Geometric 50 0 39 9.32 65.7 466 EnvStats_MVUE 0.0951 +#> 1 Geometric 50 0 41 11.1 101. 554 EnvStats_MME 0.0828 +#> 2 Geometric 50 0 41 11.1 101. 554 EnvStats_MVUE 0.0813 output$combined_data_tbl %>% tidy_combined_autoplot() diff --git a/docs/reference/util_hypergeometric_param_estimate-1.png b/docs/reference/util_hypergeometric_param_estimate-1.png index b0e5e5d4..0ad2f675 100644 Binary files a/docs/reference/util_hypergeometric_param_estimate-1.png and b/docs/reference/util_hypergeometric_param_estimate-1.png differ diff --git a/docs/reference/util_hypergeometric_param_estimate.html b/docs/reference/util_hypergeometric_param_estimate.html index d78ff1ff..47498beb 100644 --- a/docs/reference/util_hypergeometric_param_estimate.html +++ b/docs/reference/util_hypergeometric_param_estimate.html @@ -166,8 +166,8 @@

    Examples#> # A tibble: 2 × 5 #> dist_type samp_size method m total #> <chr> <int> <chr> <dbl> <dbl> -#> 1 Hypergeometric 10 EnvStats_MLE 30.6 NA -#> 2 Hypergeometric 10 EnvStats_MVUE 30 50 +#> 1 Hypergeometric 10 EnvStats_MLE 10.2 NA +#> 2 Hypergeometric 10 EnvStats_MVUE 10 50 output$combined_data_tbl %>% tidy_combined_autoplot() diff --git a/docs/reference/util_logistic_param_estimate-1.png b/docs/reference/util_logistic_param_estimate-1.png index eaae6fca..ef9ef364 100644 Binary files a/docs/reference/util_logistic_param_estimate-1.png and b/docs/reference/util_logistic_param_estimate-1.png differ diff --git a/docs/reference/util_logistic_param_estimate.html b/docs/reference/util_logistic_param_estimate.html index 9d58c46b..0172b28b 100644 --- a/docs/reference/util_logistic_param_estimate.html +++ b/docs/reference/util_logistic_param_estimate.html @@ -165,9 +165,9 @@

    Examples#> # A tibble: 3 × 10 #> dist_type samp_size min max mean basic_scale method locat…¹ scale shape…² #> <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Logistic 50 -5.04 7.41 2.23 1.41 EnvSt… 2.23 1.41 1.58 -#> 2 Logistic 50 -5.04 7.41 2.23 1.41 EnvSt… 2.23 1.43 1.56 -#> 3 Logistic 50 -5.04 7.41 2.23 1.41 EnvSt… 2.23 1.65 1.35 +#> 1 Logistic 50 -3.77 9.27 3.03 1.35 EnvSt… 3.03 1.35 2.24 +#> 2 Logistic 50 -3.77 9.27 3.03 1.35 EnvSt… 3.03 1.37 2.22 +#> 3 Logistic 50 -3.77 9.27 3.03 1.35 EnvSt… 3.03 1.86 1.63 #> # … with abbreviated variable names ¹​location, ²​shape_ratio diff --git a/docs/reference/util_logistic_stats_tbl.html b/docs/reference/util_logistic_stats_tbl.html index 14e0f6ff..7d2c24da 100644 --- a/docs/reference/util_logistic_stats_tbl.html +++ b/docs/reference/util_logistic_stats_tbl.html @@ -134,10 +134,10 @@

    Examples#> $ coeff_var <dbl> 3.289868 #> $ skewness <dbl> 0 #> $ kurtosis <dbl> 1.2 -#> $ computed_std_skew <dbl> 0.4760057 -#> $ computed_std_kurt <dbl> 3.253218 -#> $ ci_lo <dbl> -2.845881 -#> $ ci_hi <dbl> 4.53937 +#> $ computed_std_skew <dbl> -0.244126 +#> $ computed_std_kurt <dbl> 3.542863 +#> $ ci_lo <dbl> -3.169252 +#> $ ci_hi <dbl> 3.057175 diff --git a/docs/reference/util_lognormal_param_estimate-1.png b/docs/reference/util_lognormal_param_estimate-1.png index 57beb98a..8aca7208 100644 Binary files a/docs/reference/util_lognormal_param_estimate-1.png and b/docs/reference/util_lognormal_param_estimate-1.png differ diff --git a/docs/reference/util_lognormal_param_estimate.html b/docs/reference/util_lognormal_param_estimate.html index f6e67544..57313ba6 100644 --- a/docs/reference/util_lognormal_param_estimate.html +++ b/docs/reference/util_lognormal_param_estimate.html @@ -159,8 +159,8 @@

    Examples#> # A tibble: 2 × 8 #> dist_type samp_size min max method mean_log sd_log shape_ratio #> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Lognormal 50 0.721 97.7 EnvStats_MVUE 1.84 1.13 1.64 -#> 2 Lognormal 50 0.721 97.7 EnvStats_MME 1.84 1.12 1.65 +#> 1 Lognormal 50 0.645 98.5 EnvStats_MVUE 2.02 1.25 1.62 +#> 2 Lognormal 50 0.645 98.5 EnvStats_MME 2.02 1.24 1.64 diff --git a/docs/reference/util_lognormal_stats_tbl.html b/docs/reference/util_lognormal_stats_tbl.html index 0f5e40b1..d1269d9d 100644 --- a/docs/reference/util_lognormal_stats_tbl.html +++ b/docs/reference/util_lognormal_stats_tbl.html @@ -134,10 +134,10 @@

    Examples#> $ coeff_var <dbl> 1.310832 #> $ skewness <dbl> 6.184877 #> $ kurtosis <dbl> 113.9364 -#> $ computed_std_skew <dbl> 1.816789 -#> $ computed_std_kurt <dbl> 5.833297 -#> $ ci_lo <dbl> 0.1131009 -#> $ ci_hi <dbl> 5.867792 +#> $ computed_std_skew <dbl> 5.231007 +#> $ computed_std_kurt <dbl> 33.27799 +#> $ ci_lo <dbl> 0.1049607 +#> $ ci_hi <dbl> 5.759606 diff --git a/docs/reference/util_negative_binomial_param_estimate-1.png b/docs/reference/util_negative_binomial_param_estimate-1.png index ed61574c..d76654ba 100644 Binary files a/docs/reference/util_negative_binomial_param_estimate-1.png and b/docs/reference/util_negative_binomial_param_estimate-1.png differ diff --git a/docs/reference/util_negative_binomial_param_estimate.html b/docs/reference/util_negative_binomial_param_estimate.html index 08158e07..16acf9db 100644 --- a/docs/reference/util_negative_binomial_param_estimate.html +++ b/docs/reference/util_negative_binomial_param_estimate.html @@ -166,10 +166,10 @@

    Examplest <- rnbinom(50, 1, .1) util_negative_binomial_param_estimate(t, .size = 1)$parameter_tbl #> # A tibble: 2 × 9 -#> dist_type samp_size min max mean method size prob shape…¹ -#> <chr> <int> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Negative Binomial 50 0 26 8.7 EnvStats_MM… 50 0.103 485 -#> 2 Negative Binomial 50 0 26 8.7 EnvStats_MM… 50 0.101 494. +#> dist_type samp_size min max mean method size prob shape…¹ +#> <chr> <int> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> +#> 1 Negative Binomial 50 0 44 10.2 EnvStats_M… 50 0.0891 561 +#> 2 Negative Binomial 50 0 44 10.2 EnvStats_M… 50 0.0875 571. #> # … with abbreviated variable name ¹​shape_ratio diff --git a/docs/reference/util_negative_binomial_stats_tbl.html b/docs/reference/util_negative_binomial_stats_tbl.html index cbc2d13c..1a70377e 100644 --- a/docs/reference/util_negative_binomial_stats_tbl.html +++ b/docs/reference/util_negative_binomial_stats_tbl.html @@ -119,7 +119,7 @@

    Examples#> Columns: 17 #> $ tidy_function <chr> "tidy_negative_binomial" #> $ function_call <chr> "Negative Binomial c(1, 0.1)" -#> $ distribution <chr> "Negative_binomial" +#> $ distribution <chr> "Negative Binomial" #> $ distribution_type <chr> "discrete" #> $ points <dbl> 50 #> $ simulations <dbl> 1 @@ -130,10 +130,10 @@

    Examples#> $ coeff_var <dbl> 0.1234568 #> $ skewness <dbl> 3.478505 #> $ kurtosis <dbl> 14.1 -#> $ computed_std_skew <dbl> 1.244179 -#> $ computed_std_kurt <dbl> 4.68958 +#> $ computed_std_skew <dbl> 1.579481 +#> $ computed_std_kurt <dbl> 5.00942 #> $ ci_lo <dbl> 0 -#> $ ci_hi <dbl> 26.75 +#> $ ci_hi <dbl> 49.975 diff --git a/docs/reference/util_normal_param_estimate-1.png b/docs/reference/util_normal_param_estimate-1.png index b62efdc3..a0801db5 100644 Binary files a/docs/reference/util_normal_param_estimate-1.png and b/docs/reference/util_normal_param_estimate-1.png differ diff --git a/docs/reference/util_normal_param_estimate.html b/docs/reference/util_normal_param_estimate.html index a688f8de..35a4dd8d 100644 --- a/docs/reference/util_normal_param_estimate.html +++ b/docs/reference/util_normal_param_estimate.html @@ -158,10 +158,10 @@

    Examplest <- rnorm(50, 0, 1) util_normal_param_estimate(t)$parameter_tbl #> # A tibble: 2 × 8 -#> dist_type samp_size min max method mu stan_dev shape_ratio -#> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Gaussian 50 -1.94 2.54 EnvStats_MME_MLE 0.105 0.959 0.109 -#> 2 Gaussian 50 -1.94 2.54 EnvStats_MVUE 0.105 0.968 0.108 +#> dist_type samp_size min max method mu stan_dev shape_ratio +#> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> +#> 1 Gaussian 50 -2.09 2.19 EnvStats_MME_MLE -0.109 1.00 -0.109 +#> 2 Gaussian 50 -2.09 2.19 EnvStats_MVUE -0.109 1.01 -0.108 diff --git a/docs/reference/util_normal_stats_tbl.html b/docs/reference/util_normal_stats_tbl.html index 60b14541..f01e13ae 100644 --- a/docs/reference/util_normal_stats_tbl.html +++ b/docs/reference/util_normal_stats_tbl.html @@ -128,16 +128,16 @@

    Examples#> $ points <dbl> 50 #> $ simulations <dbl> 1 #> $ mean <dbl> 0 -#> $ median <dbl> 0.1488648 +#> $ median <dbl> 0.2399192 #> $ mode <dbl> 0 #> $ std_dv <dbl> 1 #> $ coeff_var <dbl> Inf #> $ skewness <dbl> 0 #> $ kurtosis <dbl> 3 -#> $ computed_std_skew <dbl> -0.3345225 -#> $ computed_std_kurt <dbl> 2.859214 -#> $ ci_lo <dbl> -2.083379 -#> $ ci_hi <dbl> 1.850531 +#> $ computed_std_skew <dbl> -0.2225466 +#> $ computed_std_kurt <dbl> 2.929565 +#> $ ci_lo <dbl> -1.859047 +#> $ ci_hi <dbl> 1.949315 diff --git a/docs/reference/util_pareto_param_estimate-1.png b/docs/reference/util_pareto_param_estimate-1.png index 290bcc1b..673a1b9c 100644 Binary files a/docs/reference/util_pareto_param_estimate-1.png and b/docs/reference/util_pareto_param_estimate-1.png differ diff --git a/docs/reference/util_pareto_param_estimate.html b/docs/reference/util_pareto_param_estimate.html index ed70ab26..3f5f596a 100644 --- a/docs/reference/util_pareto_param_estimate.html +++ b/docs/reference/util_pareto_param_estimate.html @@ -160,10 +160,10 @@

    Examplest <- tidy_pareto(50, 1, 1) %>% pull(y) util_pareto_param_estimate(t)$parameter_tbl #> # A tibble: 2 × 8 -#> dist_type samp_size min max method shape scale shape_ratio -#> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Pareto 50 0.00883 60.5 LSE 0.0764 0.402 0.190 -#> 2 Pareto 50 0.00883 60.5 MLE 0.00883 0.217 0.0407 +#> dist_type samp_size min max method shape scale shape_ratio +#> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> +#> 1 Pareto 50 0.0877 71.3 LSE 0.248 0.688 0.361 +#> 2 Pareto 50 0.0877 71.3 MLE 0.0877 0.405 0.217 diff --git a/docs/reference/util_pareto_stats_tbl.html b/docs/reference/util_pareto_stats_tbl.html index 7a4e2d59..ae70f3ee 100644 --- a/docs/reference/util_pareto_stats_tbl.html +++ b/docs/reference/util_pareto_stats_tbl.html @@ -136,10 +136,10 @@

    Examples#> $ coeff_var <dbl> 0.000154321 #> $ skewness <dbl> 2.811057 #> $ kurtosis <dbl> 14.82857 -#> $ computed_std_skew <dbl> 1.309907 -#> $ computed_std_kurt <dbl> 4.325999 -#> $ ci_lo <dbl> 0.0002655451 -#> $ ci_hi <dbl> 0.02473998 +#> $ computed_std_skew <dbl> 1.351763 +#> $ computed_std_kurt <dbl> 4.764217 +#> $ ci_lo <dbl> 0.0004912303 +#> $ ci_hi <dbl> 0.0368343 diff --git a/docs/reference/util_poisson_param_estimate-1.png b/docs/reference/util_poisson_param_estimate-1.png index 60978e06..51c9aa0f 100644 Binary files a/docs/reference/util_poisson_param_estimate-1.png and b/docs/reference/util_poisson_param_estimate-1.png differ diff --git a/docs/reference/util_poisson_param_estimate.html b/docs/reference/util_poisson_param_estimate.html index 5bff016c..b2ff9099 100644 --- a/docs/reference/util_poisson_param_estimate.html +++ b/docs/reference/util_poisson_param_estimate.html @@ -147,7 +147,7 @@

    Examples#> # A tibble: 1 × 6 #> dist_type samp_size min max method lambda #> <chr> <int> <dbl> <dbl> <chr> <dbl> -#> 1 Posson 50 1 12 MLE 5 +#> 1 Posson 50 0 9 MLE 5.02 diff --git a/docs/reference/util_poisson_stats_tbl.html b/docs/reference/util_poisson_stats_tbl.html index 891c5d74..3d7351b9 100644 --- a/docs/reference/util_poisson_stats_tbl.html +++ b/docs/reference/util_poisson_stats_tbl.html @@ -134,8 +134,8 @@

    Examples#> $ coeff_var <dbl> 1 #> $ skewness <dbl> 1 #> $ kurtosis <dbl> 4 -#> $ computed_std_skew <dbl> 0.9399507 -#> $ computed_std_kurt <dbl> 3.280704 +#> $ computed_std_skew <dbl> 0.5753952 +#> $ computed_std_kurt <dbl> 2.484442 #> $ ci_lo <dbl> 0 #> $ ci_hi <dbl> 3 diff --git a/docs/reference/util_t_stats_tbl.html b/docs/reference/util_t_stats_tbl.html index 3cf65ef8..d9d29c76 100644 --- a/docs/reference/util_t_stats_tbl.html +++ b/docs/reference/util_t_stats_tbl.html @@ -121,7 +121,7 @@

    Examples#> Columns: 17 #> $ tidy_function <chr> "tidy_t" #> $ function_call <chr> "T Distribution c(1, 0)" -#> $ distribution <chr> "T" +#> $ distribution <chr> "t" #> $ distribution_type <chr> "continuous" #> $ points <dbl> 50 #> $ simulations <dbl> 1 @@ -132,10 +132,10 @@

    Examples#> $ coeff_var <chr> "undefined" #> $ skewness <dbl> 0 #> $ kurtosis <chr> "undefined" -#> $ computed_std_skew <dbl> -6.267111 -#> $ computed_std_kurt <dbl> 42.42918 -#> $ ci_lo <dbl> -20.13772 -#> $ ci_hi <dbl> 5.176328 +#> $ computed_std_skew <dbl> 3.492746 +#> $ computed_std_kurt <dbl> 16.59944 +#> $ ci_lo <dbl> -6.492515 +#> $ ci_hi <dbl> 26.14414 diff --git a/docs/reference/util_uniform_param_estimate-1.png b/docs/reference/util_uniform_param_estimate-1.png index 1bfc372b..b0b5d120 100644 Binary files a/docs/reference/util_uniform_param_estimate-1.png and b/docs/reference/util_uniform_param_estimate-1.png differ diff --git a/docs/reference/util_uniform_param_estimate.html b/docs/reference/util_uniform_param_estimate.html index d5ca5e89..f579076e 100644 --- a/docs/reference/util_uniform_param_estimate.html +++ b/docs/reference/util_uniform_param_estimate.html @@ -135,8 +135,8 @@

    Examples#> # A tibble: 2 × 8 #> dist_type samp_size min max method min_est max_est ratio #> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Uniform 50 1.04 2.81 NIST_MME 1.02 2.78 0.366 -#> 2 Uniform 50 1.04 2.81 NIST_MLE 1 3 0.333 +#> 1 Uniform 50 1.01 2.93 NIST_MME 1.06 2.98 0.355 +#> 2 Uniform 50 1.01 2.93 NIST_MLE 1 3 0.333 output$combined_data_tbl %>% tidy_combined_autoplot() diff --git a/docs/reference/util_uniform_stats_tbl.html b/docs/reference/util_uniform_stats_tbl.html index 3e55ad12..afebd7a9 100644 --- a/docs/reference/util_uniform_stats_tbl.html +++ b/docs/reference/util_uniform_stats_tbl.html @@ -132,10 +132,10 @@

    Examples#> $ coeff_var <dbl> 0.5773503 #> $ skewness <dbl> 0 #> $ kurtosis <dbl> 1.8 -#> $ computed_std_skew <dbl> -0.4269857 -#> $ computed_std_kurt <dbl> 2.328649 -#> $ ci_lo <dbl> 0.04275606 -#> $ ci_hi <dbl> 0.9214472 +#> $ computed_std_skew <dbl> 0.2448167 +#> $ computed_std_kurt <dbl> 1.741354 +#> $ ci_lo <dbl> 0.01871572 +#> $ ci_hi <dbl> 0.9429315 diff --git a/docs/reference/util_weibull_param_estimate-1.png b/docs/reference/util_weibull_param_estimate-1.png index 4e0f10a1..ee2d4544 100644 Binary files a/docs/reference/util_weibull_param_estimate-1.png and b/docs/reference/util_weibull_param_estimate-1.png differ diff --git a/docs/reference/util_weibull_param_estimate.html b/docs/reference/util_weibull_param_estimate.html index d785dbd1..6e1ea926 100644 --- a/docs/reference/util_weibull_param_estimate.html +++ b/docs/reference/util_weibull_param_estimate.html @@ -136,7 +136,7 @@

    Examples#> # A tibble: 1 × 8 #> dist_type samp_size min max method shape scale shape_ratio #> <chr> <int> <dbl> <dbl> <chr> <dbl> <dbl> <dbl> -#> 1 Weibull 50 0.0411 6.99 NIST 1.10 2.19 0.504 +#> 1 Weibull 50 0.0286 8.68 NIST 1.00 1.96 0.510 output$combined_data_tbl %>% tidy_combined_autoplot() diff --git a/docs/reference/util_weibull_stats_tbl.html b/docs/reference/util_weibull_stats_tbl.html index eb5f8440..72967297 100644 --- a/docs/reference/util_weibull_stats_tbl.html +++ b/docs/reference/util_weibull_stats_tbl.html @@ -127,16 +127,16 @@

    Examples#> $ distribution_type <chr> "continuous" #> $ points <dbl> 50 #> $ simulations <dbl> 1 -#> $ mean <dbl> 1.256003 -#> $ median <dbl> 1.134406 +#> $ mean <dbl> 1.222403 +#> $ median <dbl> 0.8184428 #> $ mode <dbl> 0 #> $ range <chr> "0 to Inf" -#> $ std_dv <dbl> 1.166261 -#> $ coeff_var <dbl> 1.360165 -#> $ computed_std_skew <dbl> 1.185473 -#> $ computed_std_kurt <dbl> 4.728838 -#> $ ci_lo <dbl> 0.05001485 -#> $ ci_hi <dbl> 3.80199 +#> $ std_dv <dbl> 1.128565 +#> $ coeff_var <dbl> 1.27366 +#> $ computed_std_skew <dbl> 1.152611 +#> $ computed_std_kurt <dbl> 3.774209 +#> $ ci_lo <dbl> 0.05912578 +#> $ ci_hi <dbl> 3.336329 diff --git a/docs/search.json b/docs/search.json index f8434612..77db5885 100644 --- a/docs/search.json +++ b/docs/search.json @@ -1 +1 @@ -[{"path":"https://www.spsanderson.com/TidyDensity/articles/getting-started.html","id":"example","dir":"Articles","previous_headings":"","what":"Example","title":"Getting Started with TidyDensity","text":"basic example shows easy generate data TidyDensity: example plot tidy_normal data. can also take look plots number simulations greater nine. automatically turn legend become noisy.","code":"library(TidyDensity) library(dplyr) library(ggplot2) tidy_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.497 -3.23 0.000378 0.690 0.497 #> 2 1 2 -0.660 -3.10 0.000998 0.255 -0.660 #> 3 1 3 -0.813 -2.97 0.00236 0.208 -0.813 #> 4 1 4 0.0533 -2.84 0.00498 0.521 0.0533 #> 5 1 5 0.664 -2.72 0.00944 0.747 0.664 #> 6 1 6 -0.861 -2.59 0.0161 0.195 -0.861 #> 7 1 7 0.308 -2.46 0.0246 0.621 0.308 #> 8 1 8 1.37 -2.33 0.0341 0.914 1.37 #> 9 1 9 -1.34 -2.20 0.0433 0.0897 -1.34 #> 10 1 10 0.685 -2.08 0.0512 0.753 0.685 #> # … with 40 more rows tn <- tidy_normal(.n = 100, .num_sims = 6) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\") tn <- tidy_normal(.n = 100, .num_sims = 20) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Steven Sanderson. Author, maintainer. Steven Sanderson. Copyright holder.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Sanderson S (2022). TidyDensity: Functions Tidy Analysis Generation Random Data. R package version 1.2.3.9000, https://github.com/spsanderson/TidyDensity.","code":"@Manual{, title = {TidyDensity: Functions for Tidy Analysis and Generation of Random Data}, author = {Steven Sanderson}, year = {2022}, note = {R package version 1.2.3.9000}, url = {https://github.com/spsanderson/TidyDensity}, }"},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"our-pledge","dir":"","previous_headings":"","what":"Our Pledge","title":"Contributor Covenant Code of Conduct","text":"members, contributors, leaders pledge make participation community harassment-free experience everyone, regardless age, body size, visible invisible disability, ethnicity, sex characteristics, gender identity expression, level experience, education, socio-economic status, nationality, personal appearance, race, religion, sexual identity orientation. pledge act interact ways contribute open, welcoming, diverse, inclusive, healthy community.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"our-standards","dir":"","previous_headings":"","what":"Our Standards","title":"Contributor Covenant Code of Conduct","text":"Examples behavior contributes positive environment community include: Demonstrating empathy kindness toward people respectful differing opinions, viewpoints, experiences Giving gracefully accepting constructive feedback Accepting responsibility apologizing affected mistakes, learning experience Focusing best just us individuals, overall community Examples unacceptable behavior include: use sexualized language imagery, sexual attention advances kind Trolling, insulting derogatory comments, personal political attacks Public private harassment Publishing others’ private information, physical email address, without explicit permission conduct reasonably considered inappropriate professional setting","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"enforcement-responsibilities","dir":"","previous_headings":"","what":"Enforcement Responsibilities","title":"Contributor Covenant Code of Conduct","text":"Community leaders responsible clarifying enforcing standards acceptable behavior take appropriate fair corrective action response behavior deem inappropriate, threatening, offensive, harmful. Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement spsanderson@gmail.com. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"id_1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"id_2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. Violating terms may lead temporary permanent ban.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"id_3-temporary-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"3. Temporary Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: serious violation community standards, including sustained inappropriate behavior. Consequence: temporary ban sort interaction public communication community specified period time. public private interaction people involved, including unsolicited interaction enforcing Code Conduct, allowed period. Violating terms may lead permanent ban.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"id_4-permanent-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"4. Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.0, available https://www.contributor-covenant.org/version/2/0/code_of_conduct.html. Community Impact Guidelines inspired Mozilla’s code conduct enforcement ladder. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https://www.contributor-covenant.org/translations.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/index.html","id":"tidydensity-","dir":"","previous_headings":"","what":"Functions for Tidy Analysis and Generation of Random Data","title":"Functions for Tidy Analysis and Generation of Random Data","text":"goal TidyDensity make working random numbers different distributions easy. tidy_ distribution functions provide following components: [r_] [d_] [q_] [p_]","code":""},{"path":"https://www.spsanderson.com/TidyDensity/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Functions for Tidy Analysis and Generation of Random Data","text":"can install released version TidyDensity CRAN : development version GitHub :","code":"install.packages(\"TidyDensity\") # install.packages(\"devtools\") devtools::install_github(\"spsanderson/TidyDensity\")"},{"path":"https://www.spsanderson.com/TidyDensity/index.html","id":"example","dir":"","previous_headings":"","what":"Example","title":"Functions for Tidy Analysis and Generation of Random Data","text":"basic example shows solve common problem: example plot tidy_normal data. can also take look plots number simulations greater nine. automatically turn legend become noisy.","code":"library(TidyDensity) library(dplyr) library(ggplot2) tidy_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 2.01 -2.88 0.000255 0.5 Inf #> 2 1 2 -0.636 -2.76 0.000670 0.508 -0.512 #> 3 1 3 -0.317 -2.64 0.00159 0.516 -0.284 #> 4 1 4 -0.319 -2.51 0.00339 0.524 -0.285 #> 5 1 5 1.01 -2.39 0.00661 0.533 0.631 #> 6 1 6 -0.0143 -2.27 0.0118 0.541 -0.0809 #> 7 1 7 -0.431 -2.15 0.0197 0.549 -0.363 #> 8 1 8 0.430 -2.03 0.0309 0.557 0.214 #> 9 1 9 0.504 -1.90 0.0464 0.565 0.264 #> 10 1 10 -1.18 -1.78 0.0675 0.573 -0.993 #> # … with 40 more rows tn <- tidy_normal(.n = 100, .num_sims = 6) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\") tn <- tidy_normal(.n = 100, .num_sims = 20) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2022 Steven Paul Sandeson II, MPH Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_density_augment.html","id":null,"dir":"Reference","previous_headings":"","what":"Bootstrap Density Tibble — bootstrap_density_augment","title":"Bootstrap Density Tibble — bootstrap_density_augment","text":"Add density information output tidy_bootstrap(), bootstrap_unnest_tbl().","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_density_augment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bootstrap Density Tibble — bootstrap_density_augment","text":"","code":"bootstrap_density_augment(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_density_augment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Bootstrap Density Tibble — bootstrap_density_augment","text":".data data passed tidy_bootstrap() bootstrap_unnest_tbl() functions.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_density_augment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Bootstrap Density Tibble — bootstrap_density_augment","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_density_augment.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Bootstrap Density Tibble — bootstrap_density_augment","text":"function takes input output tidy_bootstrap() bootstrap_unnest_tbl() returns augmented tibble following columns added : x, y, dx, dy. looks attribute comes using tidy_bootstrap() bootstrap_unnest_tbl() work unless data comes one functions.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_density_augment.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Bootstrap Density Tibble — bootstrap_density_augment","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_density_augment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bootstrap Density Tibble — bootstrap_density_augment","text":"","code":"x <- mtcars$mpg tidy_bootstrap(x) %>% bootstrap_density_augment() #> # A tibble: 50,000 × 5 #> sim_number x y dx dy #> #> 1 1 1 17.8 4.05 0.0000865 #> 2 1 2 15.8 5.50 0.000546 #> 3 1 3 15.8 6.94 0.00228 #> 4 1 4 13.3 8.39 0.00671 #> 5 1 5 13.3 9.83 0.0156 #> 6 1 6 13.3 11.3 0.0314 #> 7 1 7 27.3 12.7 0.0543 #> 8 1 8 16.4 14.2 0.0756 #> 9 1 9 15.2 15.6 0.0839 #> 10 1 10 18.7 17.1 0.0796 #> # … with 49,990 more rows tidy_bootstrap(x) %>% bootstrap_unnest_tbl() %>% bootstrap_density_augment() #> # A tibble: 50,000 × 5 #> sim_number x y dx dy #> #> 1 1 1 21 7.53 0.000170 #> 2 1 2 22.8 8.91 0.00103 #> 3 1 3 21 10.3 0.00444 #> 4 1 4 15.8 11.7 0.0139 #> 5 1 5 18.7 13.1 0.0319 #> 6 1 6 22.8 14.4 0.0551 #> 7 1 7 33.9 15.8 0.0738 #> 8 1 8 14.3 17.2 0.0812 #> 9 1 9 17.8 18.6 0.0796 #> 10 1 10 21.4 20.0 0.0745 #> # … with 49,990 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_augment.html","id":null,"dir":"Reference","previous_headings":"","what":"Augment Bootstrap P — bootstrap_p_augment","title":"Augment Bootstrap P — bootstrap_p_augment","text":"Takes numeric vector return ecdf probability.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_augment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Augment Bootstrap P — bootstrap_p_augment","text":"","code":"bootstrap_p_augment(.data, .value, .names = \"auto\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_augment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Augment Bootstrap P — bootstrap_p_augment","text":".data data passed augmented function. .value passed rlang::enquo() capture vectors want augment. .names default \"auto\"","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_augment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Augment Bootstrap P — bootstrap_p_augment","text":"augmented tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_augment.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Augment Bootstrap P — bootstrap_p_augment","text":"Takes numeric vector return ecdf probability vector. function intended used order add columns tibble.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_augment.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Augment Bootstrap P — bootstrap_p_augment","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_augment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Augment Bootstrap P — bootstrap_p_augment","text":"","code":"x <- mtcars$mpg tidy_bootstrap(x) %>% bootstrap_unnest_tbl() %>% bootstrap_p_augment(y) #> # A tibble: 50,000 × 3 #> sim_number y p #> #> 1 1 30.4 0.936 #> 2 1 33.9 1 #> 3 1 19.7 0.561 #> 4 1 19.2 0.529 #> 5 1 19.2 0.529 #> 6 1 19.2 0.529 #> 7 1 30.4 0.936 #> 8 1 10.4 0.0607 #> 9 1 22.8 0.779 #> 10 1 30.4 0.936 #> # … with 49,990 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute Bootstrap P of a Vector — bootstrap_p_vec","title":"Compute Bootstrap P of a Vector — bootstrap_p_vec","text":"function takes vector input return ecdf probability vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute Bootstrap P of a Vector — bootstrap_p_vec","text":"","code":"bootstrap_p_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute Bootstrap P of a Vector — bootstrap_p_vec","text":".x numeric","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute Bootstrap P of a Vector — bootstrap_p_vec","text":"vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute Bootstrap P of a Vector — bootstrap_p_vec","text":"function return ecdf probability vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compute Bootstrap P of a Vector — bootstrap_p_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute Bootstrap P of a Vector — bootstrap_p_vec","text":"","code":"x <- mtcars$mpg bootstrap_p_vec(x) #> [1] 0.62500 0.62500 0.78125 0.68750 0.46875 0.43750 0.12500 0.81250 0.78125 #> [10] 0.53125 0.40625 0.34375 0.37500 0.25000 0.06250 0.06250 0.15625 0.96875 #> [19] 0.93750 1.00000 0.71875 0.28125 0.25000 0.09375 0.53125 0.87500 0.84375 #> [28] 0.93750 0.31250 0.56250 0.18750 0.68750"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_augment.html","id":null,"dir":"Reference","previous_headings":"","what":"Augment Bootstrap Q — bootstrap_q_augment","title":"Augment Bootstrap Q — bootstrap_q_augment","text":"Takes numeric vector return quantile.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_augment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Augment Bootstrap Q — bootstrap_q_augment","text":"","code":"bootstrap_q_augment(.data, .value, .names = \"auto\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_augment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Augment Bootstrap Q — bootstrap_q_augment","text":".data data passed augmented function. .value passed rlang::enquo() capture vectors want augment. .names default \"auto\"","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_augment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Augment Bootstrap Q — bootstrap_q_augment","text":"augmented tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_augment.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Augment Bootstrap Q — bootstrap_q_augment","text":"Takes numeric vector return quantile vector. function intended used order add columns tibble.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_augment.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Augment Bootstrap Q — bootstrap_q_augment","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_augment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Augment Bootstrap Q — bootstrap_q_augment","text":"","code":"x <- mtcars$mpg tidy_bootstrap(x) %>% bootstrap_unnest_tbl() %>% bootstrap_q_augment(y) #> # A tibble: 50,000 × 3 #> sim_number y q #> #> 1 1 22.8 10.4 #> 2 1 33.9 10.4 #> 3 1 18.7 10.4 #> 4 1 26 10.4 #> 5 1 30.4 10.4 #> 6 1 17.3 10.4 #> 7 1 15.5 10.4 #> 8 1 30.4 10.4 #> 9 1 15.8 10.4 #> 10 1 32.4 10.4 #> # … with 49,990 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","title":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","text":"function takes vector input return quantile vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","text":"","code":"bootstrap_q_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","text":".x numeric","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","text":"vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","text":"function return quantile vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","text":"","code":"x <- mtcars$mpg bootstrap_q_vec(x) #> [1] 10.4 10.4 13.3 14.3 14.7 15.0 15.2 15.2 15.5 15.8 16.4 17.3 17.8 18.1 18.7 #> [16] 19.2 19.2 19.7 21.0 21.0 21.4 21.4 21.5 22.8 22.8 24.4 26.0 27.3 30.4 30.4 #> [31] 32.4 33.9"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_stat_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Bootstrap Stat Plot — bootstrap_stat_plot","title":"Bootstrap Stat Plot — bootstrap_stat_plot","text":"function produces plot cumulative statistic function applied bootstrap variable tidy_bootstrap() bootstrap_unnest_tbl() applied .","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_stat_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bootstrap Stat Plot — bootstrap_stat_plot","text":"","code":"bootstrap_stat_plot( .data, .value, .stat = \"cmean\", .show_groups = FALSE, .show_ci_labels = TRUE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_stat_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Bootstrap Stat Plot — bootstrap_stat_plot","text":".data data comes either tidy_bootstrap() bootstrap_unnest_tbl() applied . .value value column calculations applied . .stat cumulative statistic function applied .value column. must quoted. default \"cmean\". .show_groups default FALSE, set TRUE get output simulations bootstrap data. .show_ci_labels default TRUE, show last value upper lower quantile. .interactive default FALSE, set TRUE get plotly plot object back.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_stat_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Bootstrap Stat Plot — bootstrap_stat_plot","text":"plot either ggplot2 plotly.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_stat_plot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Bootstrap Stat Plot — bootstrap_stat_plot","text":"function take data either tidy_bootstrap() directly apply bootstrap_unnest_tbl() output. several different cumulative functions can applied data.accepted values : \"cmean\" - Cumulative Mean \"chmean\" - Cumulative Harmonic Mean \"cgmean\" - Cumulative Geometric Mean \"csum\" = Cumulative Sum \"cmedian\" = Cumulative Median \"cmax\" = Cumulative Max \"cmin\" = Cumulative Min \"cprod\" = Cumulative Product \"csd\" = Cumulative Standard Deviation \"cvar\" = Cumulative Variance \"cskewness\" = Cumulative Skewness \"ckurtosis\" = Cumulative Kurtotsis","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_stat_plot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Bootstrap Stat Plot — bootstrap_stat_plot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_stat_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bootstrap Stat Plot — bootstrap_stat_plot","text":"","code":"x <- mtcars$mpg tidy_bootstrap(x) %>% bootstrap_stat_plot(y, \"cmean\") tidy_bootstrap(x, .num_sims = 10) %>% bootstrap_stat_plot(y, .stat = \"chmean\", .show_groups = TRUE, .show_ci_label = FALSE ) #> Warning: Setting '.num_sims' to less than 2000 means that results can be potentially #> unstable. Consider setting to 2000 or more."},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"Unnest data output tidy_bootstrap().","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"","code":"bootstrap_unnest_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":".data data passed tidy_bootstrap() function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"function takes input output tidy_bootstrap() function returns two column tibble. columns sim_number y looks attribute comes using tidy_bootstrap() work unless data comes function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"","code":"tb <- tidy_bootstrap(.x = mtcars$mpg) bootstrap_unnest_tbl(tb) #> # A tibble: 50,000 × 2 #> sim_number y #> #> 1 1 15.8 #> 2 1 30.4 #> 3 1 19.7 #> 4 1 15.8 #> 5 1 19.2 #> 6 1 14.7 #> 7 1 14.3 #> 8 1 10.4 #> 9 1 17.8 #> 10 1 15 #> # … with 49,990 more rows bootstrap_unnest_tbl(tb) %>% tidy_distribution_summary_tbl(sim_number) #> # A tibble: 2,000 × 13 #> sim_num…¹ mean_…² media…³ std_val min_val max_val skewn…⁴ kurto…⁵ range iqr #> #> 1 1 18.1 17.8 5.38 10.4 30.4 0.824 3.37 20 5 #> 2 2 20.6 21 6.86 10.4 32.4 0.301 2.16 22 8.6 #> 3 3 19.5 19.2 5.87 10.4 33.9 0.816 3.34 23.5 5.9 #> 4 4 19.5 21 5.52 10.4 33.9 0.255 3.33 23.5 6.3 #> 5 5 19.8 18.1 6.70 10.4 33.9 0.906 2.75 23.5 9.2 #> 6 6 18.0 16.4 5.66 10.4 33.9 1.06 4.22 23.5 6.7 #> 7 7 19.8 18.1 6.83 10.4 33.9 0.833 2.78 23.5 6.8 #> 8 8 18.7 17.8 5.46 10.4 32.4 0.935 3.54 22 5.8 #> 9 9 19.0 19.2 5.35 10.4 33.9 0.694 3.74 23.5 6.4 #> 10 10 20.7 21 5.62 13.3 30.4 0.396 1.99 17.1 6.4 #> # … with 1,990 more rows, 3 more variables: variance , ci_low , #> # ci_high , and abbreviated variable names ¹​sim_number, ²​mean_val, #> # ³​median_val, ⁴​skewness, ⁵​kurtosis"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cgmean.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Geometric Mean — cgmean","title":"Cumulative Geometric Mean — cgmean","text":"function return cumulative geometric mean vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cgmean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Geometric Mean — cgmean","text":"","code":"cgmean(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cgmean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Geometric Mean — cgmean","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cgmean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Geometric Mean — cgmean","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cgmean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Geometric Mean — cgmean","text":"function return cumulative geometric mean vector. exp(cummean(log(.x)))","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/cgmean.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Geometric Mean — cgmean","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cgmean.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Geometric Mean — cgmean","text":"","code":"x <- mtcars$mpg cgmean(x) #> [1] 21.00000 21.00000 21.58363 21.53757 20.93755 20.43547 19.41935 19.98155 #> [9] 20.27666 20.16633 19.93880 19.61678 19.42805 19.09044 18.33287 17.69470 #> [17] 17.50275 18.11190 18.61236 19.17879 19.28342 19.09293 18.90457 18.62961 #> [25] 18.65210 18.92738 19.15126 19.46993 19.33021 19.34242 19.18443 19.25006"},{"path":"https://www.spsanderson.com/TidyDensity/reference/chmean.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Harmonic Mean — chmean","title":"Cumulative Harmonic Mean — chmean","text":"function return cumulative harmonic mean vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/chmean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Harmonic Mean — chmean","text":"","code":"chmean(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/chmean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Harmonic Mean — chmean","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/chmean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Harmonic Mean — chmean","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/chmean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Harmonic Mean — chmean","text":"function return cumulative harmonic mean vector. 1 / (cumsum(1 / .x))","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/chmean.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Harmonic Mean — chmean","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/chmean.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Harmonic Mean — chmean","text":"","code":"x <- mtcars$mpg chmean(x) #> [1] 21.0000000 10.5000000 7.1891892 5.3813575 4.1788087 3.3949947 #> [7] 2.7436247 2.4663044 2.2255626 1.9943841 1.7934398 1.6166494 #> [13] 1.4784877 1.3474251 1.1928760 1.0701322 0.9975150 0.9677213 #> [19] 0.9378663 0.9126181 0.8754572 0.8286539 0.7858140 0.7419753 #> [25] 0.7143688 0.6961523 0.6779989 0.6632076 0.6364908 0.6165699 #> [31] 0.5922267 0.5762786"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":null,"dir":"Reference","previous_headings":"","what":"Confidence Interval Generic — ci_hi","title":"Confidence Interval Generic — ci_hi","text":"Gets upper 97.5% quantile numeric vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Confidence Interval Generic — ci_hi","text":"","code":"ci_hi(.x, .na_rm = FALSE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Confidence Interval Generic — ci_hi","text":".x vector numeric values .na_rm Boolean, defaults FALSE. Passed quantile function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Confidence Interval Generic — ci_hi","text":"numeric value.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Confidence Interval Generic — ci_hi","text":"Gets upper 97.5% quantile numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Confidence Interval Generic — ci_hi","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Confidence Interval Generic — ci_hi","text":"","code":"x <- mtcars$mpg ci_hi(x) #> [1] 32.7375"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":null,"dir":"Reference","previous_headings":"","what":"Confidence Interval Generic — ci_lo","title":"Confidence Interval Generic — ci_lo","text":"Gets lower 2.5% quantile numeric vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Confidence Interval Generic — ci_lo","text":"","code":"ci_lo(.x, .na_rm = FALSE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Confidence Interval Generic — ci_lo","text":".x vector numeric values .na_rm Boolean, defaults FALSE. Passed quantile function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Confidence Interval Generic — ci_lo","text":"numeric value.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Confidence Interval Generic — ci_lo","text":"Gets lower 2.5% quantile numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Confidence Interval Generic — ci_lo","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Confidence Interval Generic — ci_lo","text":"","code":"x <- mtcars$mpg ci_lo(x) #> [1] 10.4"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ckurtosis.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Kurtosis — ckurtosis","title":"Cumulative Kurtosis — ckurtosis","text":"function return cumulative kurtosis vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ckurtosis.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Kurtosis — ckurtosis","text":"","code":"ckurtosis(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ckurtosis.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Kurtosis — ckurtosis","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ckurtosis.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Kurtosis — ckurtosis","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ckurtosis.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Kurtosis — ckurtosis","text":"function return cumulative kurtosis vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/ckurtosis.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Kurtosis — ckurtosis","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ckurtosis.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Kurtosis — ckurtosis","text":"","code":"x <- mtcars$mpg ckurtosis(x) #> [1] NaN NaN 1.500000 2.189216 2.518932 1.786006 2.744467 2.724675 #> [9] 2.930885 2.988093 2.690270 2.269038 2.176622 1.992044 2.839430 2.481896 #> [17] 2.356826 3.877115 3.174702 2.896931 3.000743 3.091225 3.182071 3.212816 #> [25] 3.352916 3.015952 2.837139 2.535185 2.595908 2.691103 2.738468 2.799467"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmean.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Mean — cmean","title":"Cumulative Mean — cmean","text":"function return cumulative mean vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Mean — cmean","text":"","code":"cmean(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Mean — cmean","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Mean — cmean","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Mean — cmean","text":"function return cumulative mean vector. uses dplyr::cummean() basis function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmean.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Mean — cmean","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmean.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Mean — cmean","text":"","code":"x <- mtcars$mpg cmean(x) #> [1] 21.00000 21.00000 21.60000 21.55000 20.98000 20.50000 19.61429 20.21250 #> [9] 20.50000 20.37000 20.13636 19.82500 19.63077 19.31429 18.72000 18.20000 #> [17] 17.99412 18.79444 19.40526 20.13000 20.19524 19.98182 19.77391 19.50417 #> [25] 19.49200 19.79231 20.02222 20.39286 20.23448 20.21667 20.04839 20.09062"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmedian.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Median — cmedian","title":"Cumulative Median — cmedian","text":"function return cumulative median vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmedian.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Median — cmedian","text":"","code":"cmedian(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmedian.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Median — cmedian","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmedian.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Median — cmedian","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmedian.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Median — cmedian","text":"function return cumulative median vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmedian.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Median — cmedian","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmedian.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Median — cmedian","text":"","code":"x <- mtcars$mpg cmedian(x) #> [1] 21.00 21.00 21.00 21.20 21.00 21.00 21.00 21.00 21.00 21.00 21.00 20.10 #> [13] 19.20 18.95 18.70 18.40 18.10 18.40 18.70 18.95 19.20 18.95 18.70 18.40 #> [25] 18.70 18.95 19.20 19.20 19.20 19.20 19.20 19.20"},{"path":"https://www.spsanderson.com/TidyDensity/reference/color_blind.html","id":null,"dir":"Reference","previous_headings":"","what":"Provide Colorblind Compliant Colors — color_blind","title":"Provide Colorblind Compliant Colors — color_blind","text":"8 Hex RGB color definitions suitable charts colorblind people.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/color_blind.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Provide Colorblind Compliant Colors — color_blind","text":"","code":"color_blind()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/csd.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Standard Deviation — csd","title":"Cumulative Standard Deviation — csd","text":"function return cumulative standard deviation vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/csd.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Standard Deviation — csd","text":"","code":"csd(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/csd.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Standard Deviation — csd","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/csd.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Standard Deviation — csd","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/csd.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Standard Deviation — csd","text":"function return cumulative standard deviation vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/csd.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Standard Deviation — csd","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/csd.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Standard Deviation — csd","text":"","code":"x <- mtcars$mpg csd(x) #> [1] NA 0.0000000 1.0392305 0.8544004 1.4737707 1.7663522 2.8445436 #> [8] 3.1302385 3.0524580 2.9070986 2.8647069 2.9366416 2.8975233 3.0252418 #> [15] 3.7142967 4.1476098 4.1046423 5.2332053 5.7405452 6.4594362 6.3029736 #> [22] 6.2319940 6.1698105 6.1772007 6.0474457 6.1199296 6.1188444 6.3166405 #> [29] 6.2611772 6.1530527 6.1217574 6.0269481"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cskewness.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Skewness — cskewness","title":"Cumulative Skewness — cskewness","text":"function return cumulative skewness vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cskewness.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Skewness — cskewness","text":"","code":"cskewness(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cskewness.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Skewness — cskewness","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cskewness.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Skewness — cskewness","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cskewness.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Skewness — cskewness","text":"function return cumulative skewness vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/cskewness.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Skewness — cskewness","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cskewness.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Skewness — cskewness","text":"","code":"x <- mtcars$mpg cskewness(x) #> [1] NaN NaN 0.707106781 0.997869718 -0.502052297 #> [6] -0.258803244 -0.867969171 -0.628239920 -0.808101715 -0.695348960 #> [11] -0.469220594 -0.256323338 -0.091505282 0.002188142 -0.519593266 #> [16] -0.512660692 -0.379598706 0.614549281 0.581410573 0.649357202 #> [21] 0.631855977 0.706212631 0.775750182 0.821447605 0.844413861 #> [26] 0.716010069 0.614326432 0.525141032 0.582528820 0.601075783 #> [31] 0.652552397 0.640439864"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cvar.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Variance — cvar","title":"Cumulative Variance — cvar","text":"function return cumulative variance vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cvar.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Variance — cvar","text":"","code":"cvar(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cvar.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Variance — cvar","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cvar.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Variance — cvar","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cvar.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Variance — cvar","text":"function return cumulative variance vector. exp(cummean(log(.x)))","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/cvar.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Variance — cvar","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cvar.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Variance — cvar","text":"","code":"x <- mtcars$mpg cvar(x) #> [1] NA 0.000000 1.080000 0.730000 2.172000 3.120000 8.091429 #> [8] 9.798393 9.317500 8.451222 8.206545 8.623864 8.395641 9.152088 #> [15] 13.796000 17.202667 16.848088 27.386438 32.953860 41.724316 39.727476 #> [22] 38.837749 38.066561 38.157808 36.571600 37.453538 37.440256 39.899947 #> [29] 39.202340 37.860057 37.475914 36.324103"},{"path":"https://www.spsanderson.com/TidyDensity/reference/dist_type_extractor.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","title":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","text":"Get distribution name title case tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/dist_type_extractor.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","text":"","code":"dist_type_extractor(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/dist_type_extractor.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","text":".x attribute list passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/dist_type_extractor.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","text":"character string","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/dist_type_extractor.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","text":"extract distribution type tidy_ distribution function output using attributes object. must pass attribute directly function. meant really used internally. passing using manually $tibble_type attribute.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/dist_type_extractor.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","text":"Steven P. Sanderson II,","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/dist_type_extractor.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","text":"","code":"tn <- tidy_normal() atb <- attributes(tn) dist_type_extractor(atb$tibble_type) #> [1] \"Gaussian\""},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_color_colorblind.html","id":null,"dir":"Reference","previous_headings":"","what":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","title":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","text":"Provide Colorblind Compliant Colors","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_color_colorblind.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","text":"","code":"td_scale_color_colorblind(..., theme = \"td\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_color_colorblind.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","text":"... Data passed function theme defaults td allowed value","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_fill_colorblind.html","id":null,"dir":"Reference","previous_headings":"","what":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","title":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","text":"Provide Colorblind Compliant Colors","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_fill_colorblind.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","text":"","code":"td_scale_fill_colorblind(..., theme = \"td\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_fill_colorblind.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","text":"... Data passed function theme defaults td allowed value","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidyeval.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy eval helpers — tidyeval","title":"Tidy eval helpers — tidyeval","text":"page lists tidy eval tools reexported package rlang. learn using tidy eval scripts packages high level, see dplyr programming vignette ggplot2 packages vignette. Metaprogramming section Advanced R may also useful deeper dive. tidy eval operators {{, !!, !!! syntactic constructs specially interpreted tidy eval functions. mostly need {{, !! !!! advanced operators use simple cases. curly-curly operator {{ allows tunnel data-variables passed function arguments inside tidy eval functions. {{ designed individual arguments. pass multiple arguments contained dots, use ... normal way. enquo() enquos() delay execution one several function arguments. former returns single expression, latter returns list expressions. defused, expressions longer evaluate . must injected back evaluation context !! (single expression) !!! (list expressions). simple case, code equivalent usage {{ ... . Defusing enquo() enquos() needed complex cases, instance need inspect modify expressions way. .data pronoun object represents current slice data. variable name string, use .data pronoun subset variable [[. Another tidy eval operator :=. makes possible use glue curly-curly syntax LHS =. technical reasons, R language support complex expressions left =, use := workaround. Many tidy eval functions like dplyr::mutate() dplyr::summarise() give automatic name unnamed inputs. need create sort automatic names , use as_label(). instance, glue-tunnelling syntax can reproduced manually : Expressions defused enquo() (tunnelled {{) need simple column names, can arbitrarily complex. as_label() handles cases gracefully. code assumes simple column name, use as_name() instead. safer throws error input name expected.","code":"my_function <- function(data, var, ...) { data %>% group_by(...) %>% summarise(mean = mean({{ var }})) } my_function <- function(data, var, ...) { # Defuse var <- enquo(var) dots <- enquos(...) # Inject data %>% group_by(!!!dots) %>% summarise(mean = mean(!!var)) } my_var <- \"disp\" mtcars %>% summarise(mean = mean(.data[[my_var]])) my_function <- function(data, var, suffix = \"foo\") { # Use `{{` to tunnel function arguments and the usual glue # operator `{` to interpolate plain strings. data %>% summarise(\"{{ var }}_mean_{suffix}\" := mean({{ var }})) } my_function <- function(data, var, suffix = \"foo\") { var <- enquo(var) prefix <- as_label(var) data %>% summarise(\"{prefix}_mean_{suffix}\" := mean(!!var)) }"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Density Data — tidy_autoplot","title":"Automatic Plot of Density Data — tidy_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq mcmc number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Density Data — tidy_autoplot","text":"","code":"tidy_autoplot( .data, .plot_type = \"density\", .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Density Data — tidy_autoplot","text":".data data passed tidy_distribution function like tidy_normal() .plot_type quoted string like 'density' .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Density Data — tidy_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Density Data — tidy_autoplot","text":"function spit one following plots: density quantile probability qq mcmc","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Density Data — tidy_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Density Data — tidy_autoplot","text":"","code":"tidy_normal(.num_sims = 5) %>% tidy_autoplot() tidy_normal(.num_sims = 20) %>% tidy_autoplot(.plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bernoulli.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","title":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","text":"function generate n random points Bernoulli distribution user provided, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bernoulli.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","text":"","code":"tidy_bernoulli(.n = 50, .prob = 0.1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bernoulli.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","text":".n number randomly generated points want. .prob probability success/failure. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bernoulli.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bernoulli.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","text":"function uses rbinom(), underlying p, d, q functions. Bernoulli distribution special case Binomial distribution size = 1 hence binom functions used set size = 1.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bernoulli.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bernoulli.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","text":"","code":"tidy_bernoulli() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1 -0.405 0.0292 1 1 #> 2 1 2 0 -0.368 0.0637 0.9 0 #> 3 1 3 0 -0.331 0.129 0.9 0 #> 4 1 4 0 -0.294 0.243 0.9 0 #> 5 1 5 0 -0.258 0.424 0.9 0 #> 6 1 6 0 -0.221 0.688 0.9 0 #> 7 1 7 1 -0.184 1.03 1 1 #> 8 1 8 0 -0.147 1.44 0.9 0 #> 9 1 9 0 -0.110 1.87 0.9 0 #> 10 1 10 0 -0.0727 2.25 0.9 0 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"function generate n random points beta distribution user provided, .shape1, .shape2, .ncp non-centrality parameter, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"","code":"tidy_beta(.n = 50, .shape1 = 1, .shape2 = 1, .ncp = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":".n number randomly generated points want. .shape1 non-negative parameter Beta distribution. .shape2 non-negative parameter Beta distribution. .ncp non-centrality parameter Beta distribution. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"function uses underlying stats::rbeta(), underlying p, d, q functions. information please see stats::rbeta()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"","code":"tidy_beta() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.741 -0.366 0.00468 0 0.791 #> 2 1 2 0.0505 -0.332 0.0107 0.0204 0.0435 #> 3 1 3 0.737 -0.297 0.0228 0.0408 0.786 #> 4 1 4 0.398 -0.263 0.0452 0.0612 0.419 #> 5 1 5 0.193 -0.229 0.0835 0.0816 0.198 #> 6 1 6 0.661 -0.195 0.144 0.102 0.704 #> 7 1 7 0.701 -0.161 0.231 0.122 0.747 #> 8 1 8 0.533 -0.126 0.347 0.143 0.566 #> 9 1 9 0.543 -0.0922 0.486 0.163 0.577 #> 10 1 10 0.0287 -0.0580 0.638 0.184 0.0199 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"function generate n random points binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"","code":"tidy_binomial(.n = 50, .size = 0, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":".n number randomly generated points want. .size Number trials, zero . .prob Probability success trial. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"function uses underlying stats::rbinom(), underlying p, d, q functions. information please see stats::rbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"","code":"tidy_binomial() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 1 NaN #> 2 1 2 0 -1.18 0.0156 1 NaN #> 3 1 3 0 -1.13 0.0220 1 NaN #> 4 1 4 0 -1.08 0.0305 1 NaN #> 5 1 5 0 -1.03 0.0418 1 NaN #> 6 1 6 0 -0.983 0.0564 1 NaN #> 7 1 7 0 -0.932 0.0749 1 NaN #> 8 1 8 0 -0.882 0.0981 1 NaN #> 9 1 9 0 -0.832 0.126 1 NaN #> 10 1 10 0 -0.781 0.161 1 NaN #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":null,"dir":"Reference","previous_headings":"","what":"Bootstrap Empirical Data — tidy_bootstrap","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"Takes input vector numeric data produces bootstrapped nested tibble simulation number.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"","code":"tidy_bootstrap( .x, .num_sims = 2000, .proportion = 0.8, .distribution_type = \"continuous\" )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Bootstrap Empirical Data — tidy_bootstrap","text":".x vector data passed function. Must numeric vector. .num_sims default 2000, can set anything desired. warning pass console value less 2000. .proportion much original data want pass sampling function. default 0.80 (80%) .distribution_type can either 'continuous' 'discrete'","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"nested tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"function take numeric input vector produce tibble bootstrapped values list. table output two columns: sim_number bootstrap_samples sim_number corresponds many times want data resampled, bootstrap_samples column contains list boostrapped resampled data.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"","code":"x <- mtcars$mpg tidy_bootstrap(x) #> # A tibble: 2,000 × 2 #> sim_number bootstrap_samples #> #> 1 1 #> 2 2 #> 3 3 #> 4 4 #> 5 5 #> 6 6 #> 7 7 #> 8 8 #> 9 9 #> 10 10 #> # … with 1,990 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"function generate n random points Burr distribution user provided, .shape1, .shape2, .scale, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"","code":"tidy_burr( .n = 50, .shape1 = 1, .shape2 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":".n number randomly generated points want. .shape1 Must strictly positive. .shape2 Must strictly positive. .rate alternative way specify .scale. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"function uses underlying actuar::rburr(), underlying p, d, q functions. information please see actuar::rburr()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"","code":"tidy_burr() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 34.6 -2.48 0.00109 0 Inf #> 2 1 2 0.0280 -1.68 0.0150 0.0200 0.000571 #> 3 1 3 0.962 -0.867 0.0855 0.0392 0.0283 #> 4 1 4 0.204 -0.0587 0.215 0.0577 0.00567 #> 5 1 5 3.08 0.749 0.266 0.0755 0.0974 #> 6 1 6 0.727 1.56 0.196 0.0926 0.0212 #> 7 1 7 1.54 2.37 0.104 0.109 0.0462 #> 8 1 8 0.593 3.17 0.0441 0.125 0.0172 #> 9 1 9 0.0464 3.98 0.0161 0.140 0.00110 #> 10 1 10 1.06 4.79 0.0167 0.155 0.0313 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"function generate n random points cauchy distribution user provided, .location, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"","code":"tidy_cauchy(.n = 50, .location = 0, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":".n number randomly generated points want. .location location parameter. .scale scale parameter, must greater equal 0. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"function uses underlying stats::rcauchy(), underlying p, d, q functions. information please see stats::rcauchy()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"","code":"tidy_cauchy() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 -10.3 -130. 2.19e- 4 0.5 1.87 #> 2 1 2 11.7 -127. 2.80e- 3 0.506 Inf #> 3 1 3 -0.0993 -124. 1.77e-11 0.513 3.71 #> 4 1 4 -1.72 -121. 3.54e-18 0.519 3.23 #> 5 1 5 -0.613 -118. 0 0.526 3.54 #> 6 1 6 0.983 -116. 7.11e-18 0.532 4.10 #> 7 1 7 0.0567 -113. 2.37e-18 0.539 3.76 #> 8 1 8 1.64 -110. 3.69e-18 0.545 4.38 #> 9 1 9 0.0626 -107. 1.63e-18 0.552 3.76 #> 10 1 10 -1.28 -104. 0 0.558 3.35 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"function generate n random points chisquare distribution user provided, .df, .ncp, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"","code":"tidy_chisquare(.n = 50, .df = 1, .ncp = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":".n number randomly generated points want. .df Degrees freedom (non-negative can non-integer) .ncp Non-centrality parameter, must non-negative. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"function uses underlying stats::rchisq(), underlying p, d, q functions. information please see stats::rchisq()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"","code":"tidy_chisquare() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 3.68 -2.25 0.00129 0 0.272 #> 2 1 2 4.08 -1.86 0.00557 0.0691 0.336 #> 3 1 3 0.259 -1.47 0.0186 0.0978 0.00135 #> 4 1 4 0.0142 -1.08 0.0483 0.120 0.00000367 #> 5 1 5 0.00115 -0.692 0.0984 0.138 0.00000000371 #> 6 1 6 5.58 -0.303 0.160 0.155 0.635 #> 7 1 7 0.000721 0.0860 0.213 0.169 0 #> 8 1 8 0.0168 0.475 0.240 0.183 0.00000521 #> 9 1 9 0.940 0.864 0.240 0.195 0.0178 #> 10 1 10 2.43 1.25 0.225 0.207 0.119 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"","code":"tidy_combined_autoplot( .data, .plot_type = \"density\", .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":".data data passed function tidy_multi_dist() .plot_type quoted string like 'density' .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"function spit one following plots: density quantile probability qq","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"","code":"combined_tbl <- tidy_combine_distributions( tidy_normal(), tidy_gamma(), tidy_beta() ) combined_tbl #> # A tibble: 150 × 8 #> sim_number x y dx dy p q dist_type #> #> 1 1 1 -0.310 -3.77 0.000266 0.378 -0.310 Gaussian c(0, 1) #> 2 1 2 -0.231 -3.61 0.000822 0.409 -0.231 Gaussian c(0, 1) #> 3 1 3 -0.440 -3.45 0.00220 0.330 -0.440 Gaussian c(0, 1) #> 4 1 4 -0.277 -3.29 0.00509 0.391 -0.277 Gaussian c(0, 1) #> 5 1 5 0.627 -3.13 0.0103 0.735 0.627 Gaussian c(0, 1) #> 6 1 6 -0.370 -2.98 0.0181 0.356 -0.370 Gaussian c(0, 1) #> 7 1 7 -0.660 -2.82 0.0283 0.255 -0.660 Gaussian c(0, 1) #> 8 1 8 -2.55 -2.66 0.0396 0.00539 -2.55 Gaussian c(0, 1) #> 9 1 9 -1.46 -2.50 0.0510 0.0720 -1.46 Gaussian c(0, 1) #> 10 1 10 1.18 -2.34 0.0624 0.880 1.18 Gaussian c(0, 1) #> # … with 140 more rows combined_tbl %>% tidy_combined_autoplot() combined_tbl %>% tidy_combined_autoplot(.plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":null,"dir":"Reference","previous_headings":"","what":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"allows user specify n number tidy_ distributions can combined single tibble. preferred method combining multiple distributions different types, example Gaussian distribution Beta distribution. generates single tibble added column dist_type give distribution family name associated parameters.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"","code":"tidy_combine_distributions(...)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"... ... can place different distributions","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"Allows user generate tibble different tidy_ distributions","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"","code":"tn <- tidy_normal() tb <- tidy_beta() tc <- tidy_cauchy() tidy_combine_distributions(tn, tb, tc) #> # A tibble: 150 × 8 #> sim_number x y dx dy p q dist_type #> #> 1 1 1 0.382 -3.62 0.000318 0.649 0.382 Gaussian c(0, 1) #> 2 1 2 -0.922 -3.47 0.000889 0.178 -0.922 Gaussian c(0, 1) #> 3 1 3 0.289 -3.33 0.00220 0.614 0.289 Gaussian c(0, 1) #> 4 1 4 1.49 -3.19 0.00484 0.931 1.49 Gaussian c(0, 1) #> 5 1 5 0.268 -3.04 0.00948 0.606 0.268 Gaussian c(0, 1) #> 6 1 6 0.557 -2.90 0.0166 0.711 0.557 Gaussian c(0, 1) #> 7 1 7 -1.53 -2.76 0.0260 0.0626 -1.53 Gaussian c(0, 1) #> 8 1 8 1.53 -2.62 0.0369 0.937 1.53 Gaussian c(0, 1) #> 9 1 9 0.361 -2.47 0.0482 0.641 0.361 Gaussian c(0, 1) #> 10 1 10 -1.37 -2.33 0.0591 0.0850 -1.37 Gaussian c(0, 1) #> # … with 140 more rows ## OR tidy_combine_distributions( tidy_normal(), tidy_beta(), tidy_cauchy(), tidy_logistic() ) #> # A tibble: 200 × 8 #> sim_number x y dx dy p q dist_type #> #> 1 1 1 -1.28 -3.43 0.000308 0.0995 -1.28 Gaussian c(0, 1) #> 2 1 2 -0.904 -3.28 0.000847 0.183 -0.904 Gaussian c(0, 1) #> 3 1 3 1.30 -3.12 0.00209 0.903 1.30 Gaussian c(0, 1) #> 4 1 4 -0.826 -2.97 0.00463 0.204 -0.826 Gaussian c(0, 1) #> 5 1 5 0.410 -2.81 0.00926 0.659 0.410 Gaussian c(0, 1) #> 6 1 6 0.456 -2.66 0.0167 0.676 0.456 Gaussian c(0, 1) #> 7 1 7 0.783 -2.50 0.0275 0.783 0.783 Gaussian c(0, 1) #> 8 1 8 -1.02 -2.35 0.0413 0.154 -1.02 Gaussian c(0, 1) #> 9 1 9 1.50 -2.20 0.0577 0.934 1.50 Gaussian c(0, 1) #> 10 1 10 -0.772 -2.04 0.0759 0.220 -0.772 Gaussian c(0, 1) #> # … with 190 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":null,"dir":"Reference","previous_headings":"","what":"Compare Empirical Data to Distributions — tidy_distribution_comparison","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"Compare empirical data set different distributions help find distribution best fit.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"","code":"tidy_distribution_comparison(.x, .distribution_type = \"continuous\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":".x data set passed function .distribution_type kind data , can one continuous discrete","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"invisible list object. tibble printed.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"purpose function take data set provided try find distribution may fit best. parameter .distribution_type must set either continuous discrete order function try appropriate types distributions. following distributions used: Continuous: tidy_beta tidy_cauchy tidy_exponential tidy_gamma tidy_logistic tidy_lognormal tidy_normal tidy_pareto tidy_uniform tidy_weibull Discrete: tidy_binomial tidy_geometric tidy_hypergeometric tidy_poisson function returns list output tibbles. tibbles returned: comparison_tbl deviance_tbl total_deviance_tbl aic_tbl kolmogorov_smirnov_tbl multi_metric_tbl comparison_tbl long tibble lists values density function given data. deviance_tbl total_deviance_tbl just give simple difference actual density estimated density given estimated distribution. aic_tbl provide AIC lm model estimated density emprical density. kolmogorov_smirnov_tbl now provides two.sided estimate ks.test estimated density empirical. multi_metric_tbl summarise metrics single tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"","code":"xc <- mtcars$mpg output_c <- tidy_distribution_comparison(xc, \"continuous\") #> For the beta distribution, its mean 'mu' should be 0 < mu < 1. The data will #> therefore be scaled to enforce this. xd <- trunc(xc) output_d <- tidy_distribution_comparison(xd, \"discrete\") output_c #> $comparison_tbl #> # A tibble: 352 × 8 #> sim_number x y dx dy p q dist_type #> #> 1 1 1 21 2.97 0.000114 0.625 10.4 Empirical #> 2 1 2 21 4.21 0.000455 0.625 10.4 Empirical #> 3 1 3 22.8 5.44 0.00142 0.781 13.3 Empirical #> 4 1 4 21.4 6.68 0.00355 0.688 14.3 Empirical #> 5 1 5 18.7 7.92 0.00721 0.469 14.7 Empirical #> 6 1 6 18.1 9.16 0.0124 0.438 15 Empirical #> 7 1 7 14.3 10.4 0.0192 0.125 15.2 Empirical #> 8 1 8 24.4 11.6 0.0281 0.812 15.2 Empirical #> 9 1 9 22.8 12.9 0.0395 0.781 15.5 Empirical #> 10 1 10 19.2 14.1 0.0516 0.531 15.8 Empirical #> # … with 342 more rows #> #> $deviance_tbl #> # A tibble: 352 × 2 #> name value #> #> 1 Empirical 0.451 #> 2 Beta c(1.11, 1.58, 0) 0.140 #> 3 Cauchy c(19.2, 7.38) 0.287 #> 4 Exponential c(0.05) 0.399 #> 5 Gamma c(11.47, 1.75) -0.545 #> 6 Logistic c(20.09, 3.27) 0.0144 #> 7 Lognormal c(2.96, 0.29) -0.126 #> 8 Pareto c(10.4, 1.62) 0.412 #> 9 Uniform c(8.34, 31.84) -0.150 #> 10 Weibull c(3.58, 22.29) 0.00581 #> # … with 342 more rows #> #> $total_deviance_tbl #> # A tibble: 10 × 2 #> dist_with_params abs_tot_deviance #> #> 1 Gaussian c(20.09, 5.93) 0.0168 #> 2 Logistic c(20.09, 3.27) 0.0168 #> 3 Beta c(1.11, 1.58, 0) 0.219 #> 4 Gamma c(11.47, 1.75) 2.13 #> 5 Lognormal c(2.96, 0.29) 2.68 #> 6 Weibull c(3.58, 22.29) 3.09 #> 7 Uniform c(8.34, 31.84) 4.30 #> 8 Exponential c(0.05) 5.67 #> 9 Cauchy c(19.2, 7.38) 7.40 #> 10 Pareto c(10.4, 1.62) 8.06 #> #> $aic_tbl #> # A tibble: 10 × 3 #> dist_type aic_value abs_aic #> #> 1 Beta c(1.11, 1.58, 0) -39.0 39.0 #> 2 Pareto c(10.4, 1.62) 86.6 86.6 #> 3 Uniform c(8.34, 31.84) -189. 189. #> 4 Lognormal c(2.96, 0.29) -189. 189. #> 5 Weibull c(3.58, 22.29) -202. 202. #> 6 Gamma c(11.47, 1.75) -229. 229. #> 7 Logistic c(20.09, 3.27) -230. 230. #> 8 Gaussian c(20.09, 5.93) -233. 233. #> 9 Cauchy c(19.2, 7.38) -234. 234. #> 10 Exponential c(0.05) -243. 243. #> #> $kolmogorov_smirnov_tbl #> # A tibble: 10 × 6 #> dist_type ks_statistic ks_pvalue ks_method alter…¹ dist_…² #> #> 1 Beta c(1.11, 1.58, 0) 0.781 0.000500 Monte-Carlo t… two-si… Beta c… #> 2 Cauchy c(19.2, 7.38) 0.75 0.000500 Monte-Carlo t… two-si… Cauchy… #> 3 Exponential c(0.05) 0.5 0.00100 Monte-Carlo t… two-si… Expone… #> 4 Gamma c(11.47, 1.75) 0.125 0.968 Monte-Carlo t… two-si… Gamma … #> 5 Logistic c(20.09, 3.27) 0.281 0.158 Monte-Carlo t… two-si… Logist… #> 6 Lognormal c(2.96, 0.29) 0.125 0.971 Monte-Carlo t… two-si… Lognor… #> 7 Pareto c(10.4, 1.62) 0.688 0.000500 Monte-Carlo t… two-si… Pareto… #> 8 Uniform c(8.34, 31.84) 0.25 0.270 Monte-Carlo t… two-si… Unifor… #> 9 Weibull c(3.58, 22.29) 0.188 0.637 Monte-Carlo t… two-si… Weibul… #> 10 Gaussian c(20.09, 5.93) 0.156 0.824 Monte-Carlo t… two-si… Gaussi… #> # … with abbreviated variable names ¹​alternative, ²​dist_char #> #> $multi_metric_tbl #> # A tibble: 10 × 8 #> dist_type abs_t…¹ aic_v…² abs_aic ks_st…³ ks_pv…⁴ ks_me…⁵ alter…⁶ #> #> 1 Gaussian c(20.09, 5.… 0.0168 -233. 233. 0.156 8.24e-1 Monte-… two-si… #> 2 Logistic c(20.09, 3.… 0.0168 -230. 230. 0.281 1.58e-1 Monte-… two-si… #> 3 Beta c(1.11, 1.58, 0) 0.219 -39.0 39.0 0.781 5.00e-4 Monte-… two-si… #> 4 Gamma c(11.47, 1.75) 2.13 -229. 229. 0.125 9.68e-1 Monte-… two-si… #> 5 Lognormal c(2.96, 0.… 2.68 -189. 189. 0.125 9.71e-1 Monte-… two-si… #> 6 Weibull c(3.58, 22.2… 3.09 -202. 202. 0.188 6.37e-1 Monte-… two-si… #> 7 Uniform c(8.34, 31.8… 4.30 -189. 189. 0.25 2.70e-1 Monte-… two-si… #> 8 Exponential c(0.05) 5.67 -243. 243. 0.5 1.00e-3 Monte-… two-si… #> 9 Cauchy c(19.2, 7.38) 7.40 -234. 234. 0.75 5.00e-4 Monte-… two-si… #> 10 Pareto c(10.4, 1.62) 8.06 86.6 86.6 0.688 5.00e-4 Monte-… two-si… #> # … with abbreviated variable names ¹​abs_tot_deviance, ²​aic_value, #> # ³​ks_statistic, ⁴​ks_pvalue, ⁵​ks_method, ⁶​alternative #> #> attr(,\".x\") #> [1] 21.0 21.0 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 17.8 16.4 17.3 15.2 10.4 #> [16] 10.4 14.7 32.4 30.4 33.9 21.5 15.5 15.2 13.3 19.2 27.3 26.0 30.4 15.8 19.7 #> [31] 15.0 21.4 #> attr(,\".n\") #> [1] 32"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"function returns summary statistics tibble. use y column tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"","code":"tidy_distribution_summary_tbl(.data, ...)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":".data data going passed tidy_ distribution function. ... grouping variable gets passed dplyr::group_by() dplyr::select().","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"summary stats tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"function takes tidy_ distribution table return tibble following information: sim_number mean_val median_val std_val min_val max_val skewness kurtosis range iqr variance ci_hi ci_lo kurtosis skewness come package healthyR.ai","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"","code":"library(dplyr) #> #> Attaching package: 'dplyr' #> The following objects are masked from 'package:stats': #> #> filter, lag #> The following objects are masked from 'package:base': #> #> intersect, setdiff, setequal, union tn <- tidy_normal(.num_sims = 5) tb <- tidy_beta(.num_sims = 5) tidy_distribution_summary_tbl(tn) #> # A tibble: 1 × 12 #> mean_val median_…¹ std_val min_val max_val skewn…² kurto…³ range iqr varia…⁴ #> #> 1 0.0118 -0.0355 0.995 -3.12 3.57 0.144 3.73 6.70 1.26 0.989 #> # … with 2 more variables: ci_low , ci_high , and abbreviated #> # variable names ¹​median_val, ²​skewness, ³​kurtosis, ⁴​variance tidy_distribution_summary_tbl(tn, sim_number) #> # A tibble: 5 × 13 #> sim_num…¹ mean_val media…² std_val min_val max_val skewn…³ kurto…⁴ range iqr #> #> 1 1 0.0466 0.0733 1.17 -2.76 3.57 0.313 3.50 6.33 1.81 #> 2 2 -0.0584 -0.242 0.796 -1.57 1.94 0.574 2.90 3.51 1.04 #> 3 3 -0.00559 -0.0498 1.02 -3.12 3.04 -0.0969 4.68 6.16 0.822 #> 4 4 0.140 0.0885 0.713 -1.57 1.42 -0.150 2.33 2.98 1.11 #> 5 5 -0.0632 -0.0256 1.20 -2.26 2.48 0.153 2.59 4.74 1.57 #> # … with 3 more variables: variance , ci_low , ci_high , and #> # abbreviated variable names ¹​sim_number, ²​median_val, ³​skewness, ⁴​kurtosis data_tbl <- tidy_combine_distributions(tn, tb) tidy_distribution_summary_tbl(data_tbl) #> # A tibble: 1 × 12 #> mean_val median_…¹ std_val min_val max_val skewn…² kurto…³ range iqr varia…⁴ #> #> 1 0.260 0.318 0.775 -3.12 3.57 -0.567 5.43 6.70 0.771 0.600 #> # … with 2 more variables: ci_low , ci_high , and abbreviated #> # variable names ¹​median_val, ²​skewness, ³​kurtosis, ⁴​variance tidy_distribution_summary_tbl(data_tbl, dist_type) #> # A tibble: 2 × 13 #> dist_type mean_…¹ media…² std_val min_val max_val skewn…³ kurto…⁴ range iqr #> #> 1 Gaussian… 0.0118 -0.0355 0.995 -3.12e+0 3.57 0.144 3.73 6.70 1.26 #> 2 Beta c(1… 0.507 0.529 0.301 7.81e-4 0.999 -0.0716 1.71 0.998 0.542 #> # … with 3 more variables: variance , ci_low , ci_high , and #> # abbreviated variable names ¹​mean_val, ²​median_val, ³​skewness, ⁴​kurtosis"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Empirical — tidy_empirical","title":"Tidy Empirical — tidy_empirical","text":"function takes single argument .x vector return tibble information similar tidy_ distribution functions. y column set equal dy density function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Empirical — tidy_empirical","text":"","code":"tidy_empirical(.x, .num_sims = 1, .distribution_type = \"continuous\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Empirical — tidy_empirical","text":".x vector numbers .num_sims many simulations run, defaults 1. .distribution_type string either \"continuous\" \"discrete\". function default \"continuous\"","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Empirical — tidy_empirical","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Empirical — tidy_empirical","text":"function takes single argument .x vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Empirical — tidy_empirical","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Empirical — tidy_empirical","text":"","code":"x <- mtcars$mpg tidy_empirical(.x = x, .distribution_type = \"continuous\") #> # A tibble: 32 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 21 2.97 0.000114 0.625 10.4 #> 2 1 2 21 4.21 0.000455 0.625 10.4 #> 3 1 3 22.8 5.44 0.00142 0.781 13.3 #> 4 1 4 21.4 6.68 0.00355 0.688 14.3 #> 5 1 5 18.7 7.92 0.00721 0.469 14.7 #> 6 1 6 18.1 9.16 0.0124 0.438 15 #> 7 1 7 14.3 10.4 0.0192 0.125 15.2 #> 8 1 8 24.4 11.6 0.0281 0.812 15.2 #> 9 1 9 22.8 12.9 0.0395 0.781 15.5 #> 10 1 10 19.2 14.1 0.0516 0.531 15.8 #> # … with 22 more rows tidy_empirical(.x = x, .num_sims = 10, .distribution_type = \"continuous\") #> # A tibble: 320 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 26 3.52 0.000124 0.844 10.4 #> 2 1 2 17.3 4.73 0.000526 0.375 10.4 #> 3 1 3 10.4 5.93 0.00172 0.0625 13.3 #> 4 1 4 30.4 7.13 0.00444 0.938 13.3 #> 5 1 5 15 8.33 0.00932 0.188 14.3 #> 6 1 6 30.4 9.53 0.0169 0.938 14.3 #> 7 1 7 14.7 10.7 0.0281 0.156 14.7 #> 8 1 8 18.7 11.9 0.0437 0.469 14.7 #> 9 1 9 33.9 13.1 0.0615 1 15 #> 10 1 10 10.4 14.3 0.0749 0.0625 15 #> # … with 310 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"function generate n random points exponential distribution user provided, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"","code":"tidy_exponential(.n = 50, .rate = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":".n number randomly generated points want. .rate vector rates .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"function uses underlying stats::rexp(), underlying p, d, q functions. information please see stats::rexp()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"","code":"tidy_exponential() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.737 -0.970 0.00143 0 0.291 #> 2 1 2 0.0211 -0.871 0.00361 0.0202 0.00537 #> 3 1 3 0.575 -0.772 0.00840 0.0400 0.219 #> 4 1 4 2.90 -0.673 0.0179 0.0594 Inf #> 5 1 5 0.170 -0.574 0.0353 0.0784 0.0585 #> 6 1 6 0.0354 -0.475 0.0639 0.0970 0.0104 #> 7 1 7 0.112 -0.376 0.107 0.115 0.0375 #> 8 1 8 1.98 -0.277 0.166 0.133 1.15 #> 9 1 9 0.872 -0.178 0.239 0.151 0.355 #> 10 1 10 0.492 -0.0795 0.321 0.168 0.184 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated F Distribution Tibble — tidy_f","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"function generate n random points rf distribution user provided, df1,df2, ncp, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"","code":"tidy_f(.n = 50, .df1 = 1, .df2 = 1, .ncp = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":".n number randomly generated points want. .df1 Degrees freedom, Inf allowed. .df2 Degrees freedom, Inf allowed. .ncp Non-centrality parameter. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"function uses underlying stats::rf(), underlying p, d, q functions. information please see stats::rf()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"","code":"tidy_f() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.425 -12.4 0.000536 0 0.000000483 #> 2 1 2 147. 7.69 0.0274 0.0903 0.0603 #> 3 1 3 15.8 27.8 0.000342 0.127 0.000666 #> 4 1 4 13.7 47.9 0.000815 0.154 0.000502 #> 5 1 5 39.9 68.0 0.000000236 0.177 0.00427 #> 6 1 6 16.1 88.1 0.00170 0.197 0.000697 #> 7 1 7 5.32 108. 0.00252 0.214 0.0000758 #> 8 1 8 0.638 128. 0.0000866 0.230 0.00000109 #> 9 1 9 2.74 148. 0.00180 0.244 0.0000201 #> 10 1 10 111. 168. 0.00000000771 0.258 0.0338 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Density Data — tidy_four_autoplot","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"","code":"tidy_four_autoplot( .data, .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":".data data passed tidy_distribution function like tidy_normal() .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"function spit one following plots: density quantile probability qq","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"","code":"tidy_normal(.num_sims = 5) %>% tidy_four_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"function generate n random points gamma distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"","code":"tidy_gamma(.n = 50, .shape = 1, .scale = 0.3, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":".n number randomly generated points want. .shape strictly 0 infinity. .scale standard deviation randomly generated data. strictly 0 infinity. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"function uses underlying stats::rgamma(), underlying p, d, q functions. information please see stats::rgamma()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"","code":"tidy_gamma() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.0195 -0.239 0.00589 0 0.00340 #> 2 1 2 0.578 -0.206 0.0194 0.0658 0.212 #> 3 1 3 0.930 -0.173 0.0553 0.127 0.511 #> 4 1 4 0.0727 -0.140 0.136 0.185 0.0181 #> 5 1 5 0.0991 -0.107 0.291 0.238 0.0256 #> 6 1 6 0.139 -0.0736 0.544 0.288 0.0375 #> 7 1 7 0.368 -0.0405 0.901 0.335 0.116 #> 8 1 8 0.220 -0.00747 1.33 0.379 0.0627 #> 9 1 9 0.144 0.0256 1.78 0.420 0.0390 #> 10 1 10 0.110 0.0587 2.17 0.458 0.0287 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"function generate n random points generalized beta distribution user provided, .shape1, .shape2, .shape3, .rate, /.sclae, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"","code":"tidy_generalized_beta( .n = 50, .shape1 = 1, .shape2 = 1, .shape3 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":".n number randomly generated points want. .shape1 non-negative parameter Beta distribution. .shape2 non-negative parameter Beta distribution. .shape3 non-negative parameter Beta distribution. .rate alternative way specify .scale parameter. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"function uses underlying stats::rbeta(), underlying p, d, q functions. information please see stats::rbeta()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"","code":"tidy_generalized_beta() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.0693 -0.387 0.00207 0 0.0556 #> 2 1 2 0.840 -0.350 0.00473 0.0204 0.845 #> 3 1 3 0.991 -0.314 0.0101 0.0408 1 #> 4 1 4 0.860 -0.278 0.0202 0.0612 0.865 #> 5 1 5 0.422 -0.241 0.0380 0.0816 0.417 #> 6 1 6 0.890 -0.205 0.0674 0.102 0.896 #> 7 1 7 0.985 -0.169 0.112 0.122 0.993 #> 8 1 8 0.368 -0.132 0.177 0.143 0.361 #> 9 1 9 0.932 -0.0960 0.264 0.163 0.939 #> 10 1 10 0.0409 -0.0597 0.373 0.184 0.0265 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"function generate n random points generalized Pareto distribution user provided, .shape1, .shape2, .rate .scale number #' random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"","code":"tidy_generalized_pareto( .n = 50, .shape1 = 1, .shape2 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":".n number randomly generated points want. .shape1 Must positive. .shape2 Must positive. .rate alternative way specify .scale argument .scale Must positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"function uses underlying actuar::rgenpareto(), underlying p, d, q functions. information please see actuar::rgenpareto()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"","code":"tidy_generalized_pareto() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.525 -1.56 0.00141 0 0.0112 #> 2 1 2 0.403 -0.548 0.122 0.02 0.00848 #> 3 1 3 0.471 0.468 0.432 0.0392 0.00997 #> 4 1 4 15.4 1.48 0.172 0.0577 0.492 #> 5 1 5 1.35 2.50 0.0455 0.0755 0.0296 #> 6 1 6 0.793 3.52 0.0268 0.0926 0.0171 #> 7 1 7 0.0438 4.53 0.0189 0.109 0.000711 #> 8 1 8 1.09 5.55 0.00902 0.125 0.0237 #> 9 1 9 1.31 6.56 0.000191 0.140 0.0286 #> 10 1 10 1.81 7.58 0.000000110 0.155 0.0402 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"function generate n random points geometric distribution user provided, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"","code":"tidy_geometric(.n = 50, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":".n number randomly generated points want. .prob probability success trial 0 < prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"function uses underlying stats::rgeom(), underlying p, d, q functions. information please see stats::rgeom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"","code":"tidy_geometric() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 1 NaN #> 2 1 2 0 -1.18 0.0156 1 NaN #> 3 1 3 0 -1.13 0.0220 1 NaN #> 4 1 4 0 -1.08 0.0305 1 NaN #> 5 1 5 0 -1.03 0.0418 1 NaN #> 6 1 6 0 -0.983 0.0564 1 NaN #> 7 1 7 0 -0.932 0.0749 1 NaN #> 8 1 8 0 -0.882 0.0981 1 NaN #> 9 1 9 0 -0.832 0.126 1 NaN #> 10 1 10 0 -0.781 0.161 1 NaN #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"function generate n random points hypergeometric distribution user provided, m,nn, k, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"","code":"tidy_hypergeometric(.n = 50, .m = 0, .nn = 0, .k = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":".n number randomly generated points want. .m number white balls urn .nn number black balls urn .k number balls drawn fro urn. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"function uses underlying stats::rhyper(), underlying p, d, q functions. information please see stats::rhyper()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"","code":"tidy_hypergeometric() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 1 NaN #> 2 1 2 0 -1.18 0.0156 1 NaN #> 3 1 3 0 -1.13 0.0220 1 NaN #> 4 1 4 0 -1.08 0.0305 1 NaN #> 5 1 5 0 -1.03 0.0418 1 NaN #> 6 1 6 0 -0.983 0.0564 1 NaN #> 7 1 7 0 -0.932 0.0749 1 NaN #> 8 1 8 0 -0.882 0.0981 1 NaN #> 9 1 9 0 -0.832 0.126 1 NaN #> 10 1 10 0 -0.781 0.161 1 NaN #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"function generate n random points Inverse Burr distribution user provided, .shape1, .shape2, .scale, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"","code":"tidy_inverse_burr( .n = 50, .shape1 = 1, .shape2 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":".n number randomly generated points want. .shape1 Must strictly positive. .shape2 Must strictly positive. .rate alternative way specify .scale. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"function uses underlying actuar::rinvburr(), underlying p, d, q functions. information please see actuar::rinvburr()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"","code":"tidy_inverse_burr() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.152 -1.51 1.50e- 3 0 0.00195 #> 2 1 2 2.82 0.00350 3.29e- 1 0.02 0.0410 #> 3 1 3 2.60 1.52 2.08e- 1 0.0392 0.0377 #> 4 1 4 0.0858 3.04 7.55e- 2 0.0577 0.00101 #> 5 1 5 0.555 4.56 2.09e- 2 0.0755 0.00766 #> 6 1 6 0.142 6.07 2.91e- 3 0.0926 0.00180 #> 7 1 7 1.73 7.59 8.38e- 3 0.109 0.0246 #> 8 1 8 0.118 9.11 4.40e- 6 0.125 0.00147 #> 9 1 9 0.166 10.6 3.57e-13 0.140 0.00215 #> 10 1 10 1.98 12.1 0 0.155 0.0284 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"function generate n random points inverse exponential distribution user provided, .rate .scale number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"","code":"tidy_inverse_exponential(.n = 50, .rate = 1, .scale = 1/.rate, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":".n number randomly generated points want. .rate alternative way specify .scale .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"function uses underlying actuar::rinvexp(), underlying p, d, q functions. information please see actuar::rinvexp()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"","code":"tidy_inverse_exponential() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.56 -2.97 0.000900 0 0.232 #> 2 1 2 0.312 -0.795 0.0809 5.24e-22 0.145 #> 3 1 3 1.30 1.38 0.204 2.29e-11 0.221 #> 4 1 4 0.531 3.56 0.0687 8.06e- 8 0.174 #> 5 1 5 0.563 5.73 0.0322 4.79e- 6 0.177 #> 6 1 6 2.94 7.91 0.0231 5.55e- 5 0.278 #> 7 1 7 0.280 10.1 0.0205 2.84e- 4 0.138 #> 8 1 8 0.387 12.3 0.00125 9.12e- 4 0.158 #> 9 1 9 1.17 14.4 0.00000756 2.19e- 3 0.215 #> 10 1 10 0.421 16.6 0.00168 4.32e- 3 0.162 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"function generate n random points inverse gamma distribution user provided, .shape, .rate, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"","code":"tidy_inverse_gamma( .n = 50, .shape = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":".n number randomly generated points want. .shape Must strictly positive. .rate alternative way specify .scale .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"function uses underlying actuar::rinvgamma(), underlying p, d, q functions. information please see actuar::rinvgamma()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"","code":"tidy_inverse_gamma() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 6.06 -4.22 0.000609 0 0.450 #> 2 1 2 6.07 -2.94 0.00662 5.24e-22 0.451 #> 3 1 3 10.7 -1.66 0.0360 2.29e-11 0.612 #> 4 1 4 1.96 -0.378 0.101 8.06e- 8 0.291 #> 5 1 5 0.449 0.902 0.151 4.79e- 6 0.182 #> 6 1 6 3.43 2.18 0.135 5.55e- 5 0.354 #> 7 1 7 0.569 3.46 0.0864 2.84e- 4 0.198 #> 8 1 8 2.63 4.74 0.0533 9.12e- 4 0.322 #> 9 1 9 1.05 6.02 0.0365 2.19e- 3 0.239 #> 10 1 10 0.401 7.30 0.0256 4.32e- 3 0.175 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"function generate n random points Inverse Gaussian distribution user provided, .mean, .shape, .dispersionThe function returns tibble simulation number column x column corresponds n randomly generated points. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"","code":"tidy_inverse_normal( .n = 50, .mean = 1, .shape = 1, .dispersion = 1/.shape, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":".n number randomly generated points want. .mean Must strictly positive. .shape Must strictly positive. .dispersion alternative way specify .shape. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"function uses underlying actuar::rinvgauss(). information please see rinvgauss()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"","code":"tidy_inverse_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 2.24 -0.565 0.00122 0 0.828 #> 2 1 2 0.516 -0.463 0.00459 6.89e-12 0.243 #> 3 1 3 3.34 -0.362 0.0147 1.98e- 6 2.13 #> 4 1 4 0.518 -0.261 0.0400 1.40e- 4 0.244 #> 5 1 5 0.678 -0.159 0.0934 1.22e- 3 0.286 #> 6 1 6 0.312 -0.0580 0.188 4.54e- 3 0.182 #> 7 1 7 0.616 0.0434 0.327 1.10e- 2 0.270 #> 8 1 8 0.791 0.145 0.497 2.09e- 2 0.316 #> 9 1 9 1.11 0.246 0.669 3.39e- 2 0.401 #> 10 1 10 0.500 0.347 0.803 4.96e- 2 0.238 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"function generate n random points inverse pareto distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"","code":"tidy_inverse_pareto(.n = 50, .shape = 1, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":".n number randomly generated points want. .shape Must positive. .scale Must positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"function uses underlying actuar::rinvpareto(), underlying p, d, q functions. information please see actuar::rinvpareto()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"","code":"tidy_inverse_pareto() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.862 -1.71 0.00111 0 0.0149 #> 2 1 2 1.47 -0.474 0.126 0.02 0.0261 #> 3 1 3 0.372 0.761 0.349 0.0392 0.00617 #> 4 1 4 0.944 2.00 0.161 0.0577 0.0164 #> 5 1 5 0.286 3.23 0.0685 0.0755 0.00465 #> 6 1 6 0.0271 4.47 0.0204 0.0926 0.0000946 #> 7 1 7 1.01 5.70 0.000918 0.109 0.0177 #> 8 1 8 40.9 6.94 0.00163 0.125 2.53 #> 9 1 9 0.245 8.17 0.0136 0.140 0.00393 #> 10 1 10 0.420 9.41 0.00129 0.155 0.00703 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"function generate n random points weibull distribution user provided, .shape, .scale, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"","code":"tidy_inverse_weibull( .n = 50, .shape = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":".n number randomly generated points want. .shape Must strictly positive. .rate alternative way specify .scale. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"function uses underlying actuar::rinvweibull(), underlying p, d, q functions. information please see actuar::rinvweibull()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"","code":"tidy_inverse_weibull() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 8.19 -2.90 8.04e- 3 0 0.202 #> 2 1 2 1.50 20.6 1.04e-14 5.24e-22 0.148 #> 3 1 3 7.23 44.2 3.83e- 3 2.29e-11 0.197 #> 4 1 4 0.140 67.7 9.89e-20 8.06e- 8 0 #> 5 1 5 2.85 91.3 0 4.79e- 6 0.165 #> 6 1 6 6.99 115. 1.28e-18 5.55e- 5 0.195 #> 7 1 7 0.843 138. 1.37e-19 2.84e- 4 0.135 #> 8 1 8 1148. 162. 0 9.12e- 4 Inf #> 9 1 9 1.92 185. 4.15e-19 2.19e- 3 0.155 #> 10 1 10 0.448 209. 8.81e-21 4.32e- 3 0.122 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"function takes vector input return kurtosis vector. length vector must least four numbers. kurtosis explains sharpness peak distribution data. ((1/n) * sum(x - mu})^4) / ((()1/n) * sum(x - mu)^2)^2","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"","code":"tidy_kurtosis_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":".x numeric vector length four .","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"kurtosis vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"function return kurtosis vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"","code":"tidy_kurtosis_vec(rnorm(100, 3, 2)) #> [1] 2.918258"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"function generate n random points logistic distribution user provided, .location, .scale, number random simulations produced. function returns tibble simulation number column x column corresonds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"","code":"tidy_logistic(.n = 50, .location = 0, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":".n number randomly generated points want. .location location parameter .scale scale parameter .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"function uses underlying stats::rlogis(), underlying p, d, q functions. information please see stats::rlogis()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"","code":"tidy_logistic() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 4.79 -5.12 0.000180 0.5 1.31 #> 2 1 2 0.931 -4.84 0.000672 0.505 -0.371 #> 3 1 3 -1.25 -4.55 0.00207 0.510 -1.42 #> 4 1 4 -3.23 -4.26 0.00533 0.515 -Inf #> 5 1 5 0.225 -3.98 0.0115 0.520 -0.668 #> 6 1 6 3.51 -3.69 0.0210 0.525 0.672 #> 7 1 7 3.70 -3.41 0.0329 0.531 0.755 #> 8 1 8 -0.399 -3.12 0.0453 0.536 -0.956 #> 9 1 9 0.281 -2.84 0.0566 0.541 -0.644 #> 10 1 10 -1.65 -2.55 0.0673 0.546 -1.70 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"function generate n random points lognormal distribution user provided, .meanlog, .sdlog, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"","code":"tidy_lognormal(.n = 50, .meanlog = 0, .sdlog = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":".n number randomly generated points want. .meanlog Mean distribution log scale default 0 .sdlog Standard deviation distribution log scale default 1 .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"function uses underlying stats::rlnorm(), underlying p, d, q functions. information please see stats::rlnorm()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"","code":"tidy_lognormal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.143 -1.22 0.00120 0 0 #> 2 1 2 1.70 -0.839 0.0124 0.0000497 0.274 #> 3 1 3 0.162 -0.458 0.0681 0.000690 0.0478 #> 4 1 4 1.38 -0.0774 0.205 0.00261 0.242 #> 5 1 5 0.631 0.303 0.355 0.00611 0.154 #> 6 1 6 2.48 0.684 0.397 0.0112 0.350 #> 7 1 7 0.221 1.06 0.352 0.0179 0.0756 #> 8 1 8 0.326 1.45 0.287 0.0258 0.103 #> 9 1 9 1.29 1.83 0.204 0.0350 0.232 #> 10 1 10 3.30 2.21 0.131 0.0451 0.428 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Mixture Data — tidy_mixture_density","title":"Tidy Mixture Data — tidy_mixture_density","text":"Create mixture model data resulting density line plots.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Mixture Data — tidy_mixture_density","text":"","code":"tidy_mixture_density(...)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Mixture Data — tidy_mixture_density","text":"... random data want pass. Example rnorm(50,0,1) something like tidy_normal(.mean = 5, .sd = 1)","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Mixture Data — tidy_mixture_density","text":"list object","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Mixture Data — tidy_mixture_density","text":"function allows make mixture model data. allows produce density data plots data strictly one family one single type distribution given set parameters. example function allow mix say tidy_normal(.mean = 0, .sd = 1) tidy_normal(.mean = 5, .sd = 1) can mix match distributions. output list object three components. Data input_data (random data passed) dist_tbl (tibble passed random data) density_tbl (tibble x y data stats::density()) Plots line_plot - Plots dist_tbl dens_plot - Plots density_tbl Input Functions input_fns - list functions parameters passed function itsefl","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Mixture Data — tidy_mixture_density","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Mixture Data — tidy_mixture_density","text":"","code":"output <- tidy_mixture_density(rnorm(100, 0, 1), tidy_normal(.mean = 5, .sd = 1)) output$data #> $dist_tbl #> # A tibble: 150 × 2 #> x y #> #> 1 1 -0.925 #> 2 2 0.889 #> 3 3 -1.05 #> 4 4 2.82 #> 5 5 0.812 #> 6 6 0.0362 #> 7 7 0.312 #> 8 8 1.10 #> 9 9 0.522 #> 10 10 0.0280 #> # … with 140 more rows #> #> $dens_tbl #> # A tibble: 150 × 2 #> x y #> #> 1 -5.12 0.0000872 #> 2 -5.02 0.000125 #> 3 -4.92 0.000176 #> 4 -4.82 0.000247 #> 5 -4.72 0.000341 #> 6 -4.62 0.000467 #> 7 -4.53 0.000634 #> 8 -4.43 0.000850 #> 9 -4.33 0.00113 #> 10 -4.23 0.00148 #> # … with 140 more rows #> #> $input_data #> $input_data$`rnorm(100, 0, 1)` #> [1] -0.92488617 0.88878323 -1.05156161 2.82410047 0.81244047 0.03623391 #> [7] 0.31179774 1.10274949 0.52232635 0.02797207 -1.31558760 -0.08488526 #> [13] 0.65891224 0.45636188 -0.09839675 0.03410962 -0.24675788 1.34399920 #> [19] 0.22207679 -1.72556965 -0.45909017 0.11793233 -0.84907589 0.14115786 #> [25] -1.39249285 -0.91418520 0.19655646 0.60103729 -2.36130537 -1.19206239 #> [31] 1.61102377 0.30940331 0.68187971 1.10216714 -0.62051860 0.21285108 #> [37] -1.47165960 -1.65637410 -0.94737206 -1.27882347 1.13353046 -0.13357788 #> [43] -1.83534254 -0.20267171 0.98907568 -0.35728433 -1.20191095 0.45702515 #> [49] -1.66654511 -0.29459664 0.65240561 -2.29879303 -1.09715605 1.05174544 #> [55] -0.39302474 0.70067363 0.47834694 -0.81458621 -1.34328261 -0.35320885 #> [61] 0.33505188 1.71093389 -0.27419588 -1.80938006 -0.92069965 1.45329888 #> [67] 0.03363828 0.07486503 -0.16234008 -0.56644185 -1.08083396 -0.56210326 #> [73] 1.40896558 0.13443725 -0.01864006 -0.81613166 0.04082222 0.22558170 #> [79] 1.11828160 1.25393824 -1.64783208 -2.49016815 -0.07012348 -0.52334032 #> [85] 0.56819673 -0.19059808 1.46029334 -0.27404032 1.39581427 -0.31427574 #> [91] 0.05568073 0.17792907 -0.62794106 1.99934604 -0.59527682 -1.51050313 #> [97] -0.98391247 -0.68410461 0.96567434 -0.98884898 #> #> $input_data$`tidy_normal(.mean = 5, .sd = 1)` #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 5.28 2.11 0.000445 0.609 5.28 #> 2 1 2 5.27 2.23 0.00130 0.606 5.27 #> 3 1 3 5.02 2.35 0.00331 0.506 5.02 #> 4 1 4 4.54 2.47 0.00740 0.324 4.54 #> 5 1 5 6.20 2.59 0.0146 0.886 6.20 #> 6 1 6 6.71 2.71 0.0255 0.956 6.71 #> 7 1 7 5.68 2.82 0.0398 0.751 5.68 #> 8 1 8 5.68 2.94 0.0561 0.751 5.68 #> 9 1 9 4.77 3.06 0.0726 0.409 4.77 #> 10 1 10 4.85 3.18 0.0879 0.442 4.85 #> # … with 40 more rows #> #> output$plots #> $line_plot #> #> $dens_plot #> output$input_fns #> [[1]] #> rnorm(100, 0, 1) #> #> [[2]] #> tidy_normal(.mean = 5, .sd = 1) #>"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"","code":"tidy_multi_dist_autoplot( .data, .plot_type = \"density\", .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":".data data passed function tidy_multi_dist() .plot_type quoted string like 'density' .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"function spit one following plots: density quantile probability qq","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"","code":"tn <- tidy_multi_single_dist( .tidy_dist = \"tidy_normal\", .param_list = list( .n = 500, .mean = c(-2, 0, 2), .sd = 1, .num_sims = 5 ) ) tn %>% tidy_multi_dist_autoplot() tn %>% tidy_multi_dist_autoplot(.plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"Generate multiple distributions data tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"","code":"tidy_multi_single_dist(.tidy_dist = NULL, .param_list = list())"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":".tidy_dist type tidy_ distribution want run. can choose one. .param_list must list() object parameters want pass TidyDensity tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"Generate multiple distributions data tidy_ distribution function. allows simulate multiple distributions family order view shapes change parameter changes. can visualize differences however choose.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"","code":"tidy_multi_single_dist( .tidy_dist = \"tidy_normal\", .param_list = list( .n = 50, .mean = c(-1, 0, 1), .sd = 1, .num_sims = 3 ) ) #> # A tibble: 450 × 8 #> sim_number dist_name x y dx dy p q #> #> 1 1 Gaussian c(-1, 1) 1 -1.13 -4.09 0.000446 0.447 -1.13 #> 2 1 Gaussian c(-1, 1) 2 -1.10 -3.97 0.00128 0.461 -1.10 #> 3 1 Gaussian c(-1, 1) 3 -1.56 -3.85 0.00321 0.288 -1.56 #> 4 1 Gaussian c(-1, 1) 4 -0.798 -3.74 0.00709 0.580 -0.798 #> 5 1 Gaussian c(-1, 1) 5 0.409 -3.62 0.0137 0.921 0.409 #> 6 1 Gaussian c(-1, 1) 6 -0.156 -3.51 0.0234 0.801 -0.156 #> 7 1 Gaussian c(-1, 1) 7 -0.894 -3.39 0.0351 0.542 -0.894 #> 8 1 Gaussian c(-1, 1) 8 -0.512 -3.27 0.0471 0.687 -0.512 #> 9 1 Gaussian c(-1, 1) 9 -1.62 -3.16 0.0569 0.267 -1.62 #> 10 1 Gaussian c(-1, 1) 10 -0.761 -3.04 0.0636 0.595 -0.761 #> # … with 440 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"function generate n random points negative binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"","code":"tidy_negative_binomial(.n = 50, .size = 1, .prob = 0.1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":".n number randomly generated points want. .size target number successful trials, dispersion parameter (shape parameter gamma mixing distribution). Must strictly positive, need integer. .prob Probability success trial 0 < .prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"function uses underlying stats::rnbinom(), underlying p, d, q functions. information please see stats::rnbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"","code":"tidy_negative_binomial() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 2 -8.98 0.000135 0.1 0 #> 2 1 2 20 -7.96 0.000388 0.1 9 #> 3 1 3 0 -6.94 0.00100 0.1 0 #> 4 1 4 4 -5.92 0.00233 0.1 1 #> 5 1 5 4 -4.90 0.00490 0.1 1 #> 6 1 6 2 -3.89 0.00931 0.1 0 #> 7 1 7 4 -2.87 0.0161 0.1 1 #> 8 1 8 5 -1.85 0.0252 0.1 1 #> 9 1 9 1 -0.826 0.0361 0.1 0 #> 10 1 10 22 0.194 0.0473 0.1 11 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"function generate n random points Gaussian distribution user provided, .mean, .sd - standard deviation number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, dnorm, pnorm qnorm data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"","code":"tidy_normal(.n = 50, .mean = 0, .sd = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":".n number randomly generated points want. .mean mean randomly generated data. .sd standard deviation randomly generated data. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"function uses underlying stats::rnorm(), stats::pnorm(), stats::qnorm() functions generate data given parameters. information please see stats::rnorm()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"","code":"tidy_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 -1.08 -3.51 0.000302 0.139 -1.08 #> 2 1 2 1.29 -3.37 0.000772 0.902 1.29 #> 3 1 3 0.0857 -3.23 0.00181 0.534 0.0857 #> 4 1 4 1.60 -3.10 0.00387 0.945 1.60 #> 5 1 5 -0.585 -2.96 0.00760 0.279 -0.585 #> 6 1 6 -1.31 -2.82 0.0137 0.0956 -1.31 #> 7 1 7 -0.684 -2.69 0.0229 0.247 -0.684 #> 8 1 8 -2.02 -2.55 0.0355 0.0217 -2.02 #> 9 1 9 1.50 -2.42 0.0513 0.933 1.50 #> 10 1 10 0.128 -2.28 0.0698 0.551 0.128 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"function generate n random points paralogistic distribution user provided, .shape, .rate, .scale number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"","code":"tidy_paralogistic( .n = 50, .shape = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":".n number randomly generated points want. .shape Must strictly positive. .rate alternative way specify .scale .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"function uses underlying actuar::rparalogis(), underlying p, d, q functions. information please see actuar::rparalogis()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"","code":"tidy_paralogistic() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.0122 -3.06 0.00103 0 0 #> 2 1 2 1.83 -2.37 0.00717 0.0200 0.0694 #> 3 1 3 2.22 -1.67 0.0320 0.0392 0.0853 #> 4 1 4 1.83 -0.969 0.0920 0.0577 0.0692 #> 5 1 5 0.580 -0.270 0.173 0.0755 0.0207 #> 6 1 6 2.20 0.428 0.217 0.0926 0.0845 #> 7 1 7 0.244 1.13 0.197 0.109 0.00834 #> 8 1 8 0.255 1.82 0.147 0.125 0.00871 #> 9 1 9 0.115 2.52 0.108 0.140 0.00369 #> 10 1 10 2.77 3.22 0.0866 0.155 0.109 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"function generate n random points pareto distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"","code":"tidy_pareto(.n = 50, .shape = 10, .scale = 0.1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":".n number randomly generated points want. .shape Must positive. .scale Must positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"function uses underlying actuar::rpareto(), underlying p, d, q functions. information please see actuar::rpareto()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"","code":"tidy_pareto() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.00685 -0.0111 0.105 0 0.00133 #> 2 1 2 0.0226 -0.00955 0.384 0.844 0.00550 #> 3 1 3 0.00811 -0.00799 1.20 0.967 0.00161 #> 4 1 4 0.0164 -0.00643 3.21 0.992 0.00364 #> 5 1 5 0.0121 -0.00486 7.34 0.997 0.00253 #> 6 1 6 0.0178 -0.00330 14.5 0.999 0.00404 #> 7 1 7 0.00183 -0.00174 24.6 1.00 0.000318 #> 8 1 8 0.0542 -0.000177 36.4 1.00 Inf #> 9 1 9 0.0125 0.00139 47.1 1.00 0.00262 #> 10 1 10 0.00384 0.00295 54.0 1.00 0.000711 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"function generate n random points single parameter pareto distribution user provided, .shape, .min, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"","code":"tidy_pareto1(.n = 50, .shape = 1, .min = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":".n number randomly generated points want. .shape Must positive. .min lower bound support distribution. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"function uses underlying actuar::rpareto1(), underlying p, d, q functions. information please see actuar::rpareto1()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"","code":"tidy_pareto1() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.24 -0.801 0.00162 0 1.00 #> 2 1 2 2.20 0.189 0.0748 0 1.03 #> 3 1 3 6.35 1.18 0.326 0 1.13 #> 4 1 4 4.10 2.17 0.259 0 1.07 #> 5 1 5 45.9 3.16 0.131 0 Inf #> 6 1 6 2.17 4.15 0.0510 0 1.03 #> 7 1 7 2.83 5.14 0.00977 0 1.04 #> 8 1 8 2.72 6.13 0.0366 0 1.04 #> 9 1 9 1.11 7.12 0.0384 0 1.00 #> 10 1 10 2.14 8.11 0.0229 0 1.03 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"function generate n random points Poisson distribution user provided, .lambda, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"","code":"tidy_poisson(.n = 50, .lambda = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":".n number randomly generated points want. .lambda vector non-negative means. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"function uses underlying stats::rpois(), underlying p, d, q functions. information please see stats::rpois()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"","code":"tidy_poisson() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.32 0.00449 0.368 0 #> 2 1 2 1 -1.18 0.0108 0.368 0 #> 3 1 3 2 -1.05 0.0235 0.368 1 #> 4 1 4 1 -0.913 0.0466 0.368 0 #> 5 1 5 1 -0.777 0.0841 0.368 0 #> 6 1 6 0 -0.642 0.138 0.368 0 #> 7 1 7 0 -0.506 0.207 0.368 0 #> 8 1 8 0 -0.371 0.282 0.368 0 #> 9 1 9 0 -0.235 0.351 0.368 0 #> 10 1 10 0 -0.0998 0.400 0.368 0 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Random Walk — tidy_random_walk","title":"Tidy Random Walk — tidy_random_walk","text":"Takes data tidy_ distribution function applies random walk calculation either cum_prod cum_sum y.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Random Walk — tidy_random_walk","text":"","code":"tidy_random_walk( .data, .initial_value = 0, .sample = FALSE, .replace = FALSE, .value_type = \"cum_prod\" )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Random Walk — tidy_random_walk","text":".data data passed tidy_ distribution function. .initial_value default 0, can set whatever want. .sample boolean value TRUE/FALSE. default FALSE. set TRUE y value tidy_ distribution function sampled. .replace boolean value TRUE/FALSE. default FALSE. set TRUE .sample set TRUE replace parameter sample function set TRUE. .value_type can take one three different values now. following: \"cum_prod\" - take cumprod y \"cum_sum\" - take cumsum y","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Random Walk — tidy_random_walk","text":"ungrouped tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Random Walk — tidy_random_walk","text":"Monte Carlo simulations first formally designed 1940’s developing nuclear weapons, since heavily used various fields use randomness solve problems potentially deterministic nature. finance, Monte Carlo simulations can useful tool give sense assets certain characteristics might behave future. complex sophisticated financial forecasting methods ARIMA (Auto-Regressive Integrated Moving Average) GARCH (Generalised Auto-Regressive Conditional Heteroskedasticity) attempt model randomness underlying macro factors seasonality volatility clustering, Monte Carlo random walks work surprisingly well illustrating market volatility long results taken seriously.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Random Walk — tidy_random_walk","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Random Walk — tidy_random_walk","text":"","code":"tidy_normal(.sd = .1, .num_sims = 25) %>% tidy_random_walk() #> # A tibble: 1,250 × 8 #> sim_number x y dx dy p q random_walk_value #> #> 1 1 1 -0.125 -0.307 0.00328 0.105 -0.125 -0.125 #> 2 1 2 -0.0905 -0.292 0.0125 0.183 -0.0905 -0.204 #> 3 1 3 0.161 -0.276 0.0391 0.946 0.161 -0.0764 #> 4 1 4 0.0463 -0.260 0.101 0.678 0.0463 -0.0336 #> 5 1 5 0.0521 -0.244 0.215 0.699 0.0521 0.0167 #> 6 1 6 -0.0336 -0.228 0.384 0.369 -0.0336 -0.0174 #> 7 1 7 0.210 -0.212 0.578 0.982 0.210 0.189 #> 8 1 8 -0.000324 -0.196 0.753 0.499 -0.000324 0.189 #> 9 1 9 -0.0361 -0.180 0.878 0.359 -0.0361 0.146 #> 10 1 10 -0.0597 -0.165 0.969 0.275 -0.0597 0.0776 #> # … with 1,240 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"auto-plotting function take tidy_ distribution function arguments regard output visualization. number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"","code":"tidy_random_walk_autoplot( .data, .line_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":".data data passed tidy_distribution function like tidy_normal() .line_size size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"function produce simple random walk plot tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"","code":"tidy_normal(.sd = .1, .num_sims = 5) %>% tidy_random_walk(.value_type = \"cum_sum\") %>% tidy_random_walk_autoplot() tidy_normal(.sd = .1, .num_sims = 20) %>% tidy_random_walk(.value_type = \"cum_sum\", .sample = TRUE, .replace = TRUE) %>% tidy_random_walk_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the range statistic — tidy_range_statistic","title":"Get the range statistic — tidy_range_statistic","text":"Takes numeric vector returns back range vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the range statistic — tidy_range_statistic","text":"","code":"tidy_range_statistic(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get the range statistic — tidy_range_statistic","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the range statistic — tidy_range_statistic","text":"single number, range statistic","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get the range statistic — tidy_range_statistic","text":"Takes numeric vector returns range vector using diff range functions.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Get the range statistic — tidy_range_statistic","text":"Steven P. Sandeson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get the range statistic — tidy_range_statistic","text":"","code":"tidy_range_statistic(seq(1:10)) #> [1] 9"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"Takes numeric vector return vector scaled [0,1]","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"","code":"tidy_scale_zero_one_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":".x numeric vector scaled [0,1] inclusive.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"Takes numeric vector return vector scaled [0,1] input vector must numeric. computation fairly straightforward. may helpful trying compare distributions data distribution like beta requires data 0 1 $$y[h] = (x - min(x))/(max(x) - min(x))$$","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"","code":"vec_1 <- rnorm(100, 2, 1) vec_2 <- tidy_scale_zero_one_vec(vec_1) dens_1 <- density(vec_1) dens_2 <- density(vec_2) max_x <- max(dens_1$x, dens_2$x) max_y <- max(dens_1$y, dens_2$y) plot(dens_1, asp = max_y / max_x, main = \"Density vec_1 (Red) and vec_2 (Blue)\", col = \"red\", xlab = \"\", ylab = \"Density of Vec 1 and Vec 2\" ) lines(dens_2, col = \"blue\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute Skewness of a Vector — tidy_skewness_vec","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"function takes vector input return skewness vector. length vector must least four numbers. skewness explains 'tailedness' distribution data. ((1/n) * sum(x - mu})^3) / ((()1/n) * sum(x - mu)^2)^(3/2)","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"","code":"tidy_skewness_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":".x numeric vector length four .","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"skewness vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"function return skewness vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"","code":"tidy_skewness_vec(rnorm(100, 3, 2)) #> [1] -0.0406822"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_stat_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","title":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","text":"function return stat function values given tidy_ distribution output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_stat_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","text":"","code":"tidy_stat_tbl( .data, .x = y, .fns, .return_type = \"vector\", .use_data_table = FALSE, ... )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_stat_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","text":".data input data coming tidy_ distribution function. .x default y can one columns input data. .fns default IQR, can stat function like quantile median etc. .return_type default \"vector\" returns sapply object. .use_data_table default FALSE, TRUE use data.table hood still return tibble. argument set TRUE .return_type parameter ignored. ... Addition function arguments supplied parameters .fns","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_stat_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","text":"return object either sapply lapply tibble based upon user input.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_stat_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","text":"function return value(s) given tidy_ distribution function output chosen column . function work tidy_ distribution functions. currently three different output types function. : \"vector\" - gives sapply() output \"list\" - gives lapply() output, \"tibble\" - returns tibble long format. Currently can pass stat function performs operation vector input. means can pass things like IQR, quantile associated arguments ... portion function. function also default rename value column tibble name function. function also give column name sim_number tibble output corresponding simulation numbers values. sapply lapply outputs column names also give simulation number information making column names like sim_number_1 etc. option .use_data_table can greatly enhance speed calculations performed used still returning tibble. calculations performed turning input data data.table object, performing necessary calculation converting back tibble object.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_stat_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_stat_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","text":"","code":"tn <- tidy_normal(.num_sims = 3) p <- c(0.025, 0.25, 0.5, 0.75, 0.95) tidy_stat_tbl(tn, y, quantile, \"vector\", probs = p, na.rm = TRUE) #> sim_number_1 sim_number_2 sim_number_3 #> 2.5% -2.06271343 -1.6858257 -1.8377483 #> 25% -0.89231070 -0.6371119 -0.9081756 #> 50% -0.05390428 -0.1477999 0.0264237 #> 75% 0.57906055 0.5406522 0.6626329 #> 95% 1.63141412 1.4790906 1.2962458 tidy_stat_tbl(tn, y, quantile, \"list\", probs = p) #> $sim_number_1 #> 2.5% 25% 50% 75% 95% #> -2.06271343 -0.89231070 -0.05390428 0.57906055 1.63141412 #> #> $sim_number_2 #> 2.5% 25% 50% 75% 95% #> -1.6858257 -0.6371119 -0.1477999 0.5406522 1.4790906 #> #> $sim_number_3 #> 2.5% 25% 50% 75% 95% #> -1.8377483 -0.9081756 0.0264237 0.6626329 1.2962458 #> tidy_stat_tbl(tn, y, quantile, \"tibble\", probs = p) #> # A tibble: 15 × 3 #> sim_number name quantile #> #> 1 1 2.5% -2.06 #> 2 1 25% -0.892 #> 3 1 50% -0.0539 #> 4 1 75% 0.579 #> 5 1 95% 1.63 #> 6 2 2.5% -1.69 #> 7 2 25% -0.637 #> 8 2 50% -0.148 #> 9 2 75% 0.541 #> 10 2 95% 1.48 #> 11 3 2.5% -1.84 #> 12 3 25% -0.908 #> 13 3 50% 0.0264 #> 14 3 75% 0.663 #> 15 3 95% 1.30 tidy_stat_tbl(tn, y, quantile, .use_data_table = TRUE, probs = p, na.rm = TRUE) #> # A tibble: 15 × 3 #> sim_number name quantile #> #> 1 1 2.5% -2.06 #> 2 1 25% -0.892 #> 3 1 50% -0.0539 #> 4 1 75% 0.579 #> 5 1 95% 1.63 #> 6 2 2.5% -1.69 #> 7 2 25% -0.637 #> 8 2 50% -0.148 #> 9 2 75% 0.541 #> 10 2 95% 1.48 #> 11 3 2.5% -1.84 #> 12 3 25% -0.908 #> 13 3 50% 0.0264 #> 14 3 75% 0.663 #> 15 3 95% 1.30"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated T Distribution Tibble — tidy_t","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"function generate n random points rt distribution user provided, df, ncp, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"","code":"tidy_t(.n = 50, .df = 1, .ncp = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":".n number randomly generated points want. .df Degrees freedom, Inf allowed. .ncp Non-centrality parameter. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"function uses underlying stats::rt(), underlying p, d, q functions. information please see stats::rt()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"","code":"tidy_t() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.0320 -64.5 2.25e- 4 0.5 3.56 #> 2 1 2 -0.338 -63.1 1.67e- 2 0.506 3.35 #> 3 1 3 -0.204 -61.6 7.37e- 5 0.513 3.42 #> 4 1 4 -4.35 -60.1 1.54e-11 0.519 1.96 #> 5 1 5 -63.1 -58.7 4.81e-18 0.526 -Inf #> 6 1 6 2.23 -57.2 2.38e-18 0.532 5.69 #> 7 1 7 -0.934 -55.7 6.37e-19 0.539 3.04 #> 8 1 8 -2.00 -54.2 0 0.545 2.61 #> 9 1 9 -0.0224 -52.8 0 0.552 3.53 #> 10 1 10 -0.910 -51.3 2.92e-19 0.558 3.06 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"function generate n random points uniform distribution user provided, .min .max values, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"","code":"tidy_uniform(.n = 50, .min = 0, .max = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":".n number randomly generated points want. .min lower limit distribution. .max upper limit distribution .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"function uses underlying stats::runif(), underlying p, d, q functions. information please see stats::runif()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"","code":"tidy_uniform() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.427 -0.352 0.00184 0 0.428 #> 2 1 2 0.776 -0.317 0.00450 0.0204 0.792 #> 3 1 3 0.972 -0.282 0.0102 0.0408 0.996 #> 4 1 4 0.520 -0.248 0.0218 0.0612 0.525 #> 5 1 5 0.877 -0.213 0.0431 0.0816 0.897 #> 6 1 6 0.253 -0.179 0.0800 0.102 0.246 #> 7 1 7 0.976 -0.144 0.139 0.122 1 #> 8 1 8 0.626 -0.109 0.226 0.143 0.635 #> 9 1 9 0.616 -0.0747 0.344 0.163 0.625 #> 10 1 10 0.397 -0.0401 0.492 0.184 0.396 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"function generate n random points weibull distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"","code":"tidy_weibull(.n = 50, .shape = 1, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":".n number randomly generated points want. .shape Shape parameter defaults 0. .scale Scale parameter defaults 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"function uses underlying stats::rweibull(), underlying p, d, q functions. information please see stats::rweibull()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"","code":"tidy_weibull() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.316 -1.20 0.00166 0 0.0833 #> 2 1 2 0.715 -1.07 0.00443 0.0202 0.200 #> 3 1 3 0.429 -0.939 0.0107 0.0400 0.115 #> 4 1 4 0.618 -0.810 0.0237 0.0594 0.170 #> 5 1 5 0.386 -0.681 0.0476 0.0784 0.103 #> 6 1 6 2.29 -0.551 0.0871 0.0970 0.874 #> 7 1 7 1.76 -0.422 0.146 0.115 0.594 #> 8 1 8 0.340 -0.293 0.225 0.133 0.0898 #> 9 1 9 0.0320 -0.164 0.318 0.151 0.00761 #> 10 1 10 0.191 -0.0346 0.414 0.168 0.0493 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"function generate n random points zero truncated binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"","code":"tidy_zero_truncated_binomial(.n = 50, .size = 0, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":".n number randomly generated points want. .size Number trials, zero . .prob Probability success trial 0 <= prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"function uses underlying actuar::rztbinom(), underlying p, d, q functions. information please see actuar::rztbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"","code":"tidy_zero_truncated_binomial() #> Warning: NaNs produced #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 NaN NaN #> 2 1 2 0 -1.18 0.0156 NaN NaN #> 3 1 3 0 -1.13 0.0220 NaN NaN #> 4 1 4 0 -1.08 0.0305 NaN NaN #> 5 1 5 0 -1.03 0.0418 NaN NaN #> 6 1 6 0 -0.983 0.0564 NaN NaN #> 7 1 7 0 -0.932 0.0749 NaN NaN #> 8 1 8 0 -0.882 0.0981 NaN NaN #> 9 1 9 0 -0.832 0.126 NaN NaN #> 10 1 10 0 -0.781 0.161 NaN NaN #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"function generate n random points zero truncated Geometric distribution user provided, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"","code":"tidy_zero_truncated_geometric(.n = 50, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":".n number randomly generated points want. .prob probability success trial 0 < prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"function uses underlying actuar::rztgeom(), underlying p, d, q functions. information please see actuar::rztgeom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"","code":"tidy_zero_truncated_geometric() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1 -0.235 0.0109 0 NaN #> 2 1 2 1 -0.184 0.0156 0 NaN #> 3 1 3 1 -0.134 0.0220 0 NaN #> 4 1 4 1 -0.0835 0.0305 0 NaN #> 5 1 5 1 -0.0331 0.0418 0 NaN #> 6 1 6 1 0.0173 0.0564 0 NaN #> 7 1 7 1 0.0677 0.0749 0 NaN #> 8 1 8 1 0.118 0.0981 0 NaN #> 9 1 9 1 0.168 0.126 0 NaN #> 10 1 10 1 0.219 0.161 0 NaN #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"function generate n random points zero truncated binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"","code":"tidy_zero_truncated_negative_binomial( .n = 50, .size = 0, .prob = 1, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":".n number randomly generated points want. .size Number trials, zero . .prob Probability success trial 0 <= prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"function uses underlying actuar::rztnbinom(), underlying p, d, q functions. information please see actuar::rztnbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"","code":"tidy_zero_truncated_binomial() #> Warning: NaNs produced #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 NaN NaN #> 2 1 2 0 -1.18 0.0156 NaN NaN #> 3 1 3 0 -1.13 0.0220 NaN NaN #> 4 1 4 0 -1.08 0.0305 NaN NaN #> 5 1 5 0 -1.03 0.0418 NaN NaN #> 6 1 6 0 -0.983 0.0564 NaN NaN #> 7 1 7 0 -0.932 0.0749 NaN NaN #> 8 1 8 0 -0.882 0.0981 NaN NaN #> 9 1 9 0 -0.832 0.126 NaN NaN #> 10 1 10 0 -0.781 0.161 NaN NaN #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"function generate n random points Zero Truncated Poisson distribution user provided, .lambda, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"","code":"tidy_zero_truncated_poisson(.n = 50, .lambda = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":".n number randomly generated points want. .lambda vector non-negative means. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"function uses underlying actuar::rztpois(), underlying p, d, q functions. information please see actuar::rztpois()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"","code":"tidy_zero_truncated_poisson() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 2 0.0786 0.00847 0 1 #> 2 1 2 3 0.157 0.0176 0 Inf #> 3 1 3 1 0.235 0.0343 0 1 #> 4 1 4 2 0.314 0.0625 0 1 #> 5 1 5 1 0.392 0.107 0 1 #> 6 1 6 1 0.471 0.171 0 1 #> 7 1 7 2 0.549 0.257 0 1 #> 8 1 8 1 0.628 0.362 0 1 #> 9 1 9 1 0.706 0.477 0 1 #> 10 1 10 3 0.784 0.589 0 Inf #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","title":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","text":"function attempt estimate Bernoulli prob parameter given vector values .x. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated Bernoulli data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","text":"","code":"util_bernoulli_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","text":".x vector data passed function. Must non-negative integers. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","text":"function see given vector .x numeric vector. attempt estimate prob parameter Bernoulli distribution.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","text":"","code":"library(dplyr) library(ggplot2) tb <- tidy_bernoulli(.prob = .1) %>% pull(y) output <- util_bernoulli_param_estimate(tb) output$parameter_tbl #> # A tibble: 1 × 8 #> dist_type samp_size min max mean variance sum_x prob #> #> 1 Bernoulli 50 0 1 0.02 0.0196 1 0.02 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_bernoulli_stats_tbl","title":"Distribution Statistics — util_bernoulli_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_bernoulli_stats_tbl","text":"","code":"util_bernoulli_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_bernoulli_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_bernoulli_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_bernoulli_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_bernoulli_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_bernoulli_stats_tbl","text":"","code":"library(dplyr) tidy_bernoulli() %>% util_bernoulli_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_bernoulli\" #> $ function_call \"Bernoulli c(0.1)\" #> $ distribution \"Bernoulli\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 0.1 #> $ mode \"0\" #> $ coeff_var 0.09 #> $ skewness 2.666667 #> $ kurtosis 5.111111 #> $ mad 0.5 #> $ entropy 0.325083 #> $ fisher_information 11.11111 #> $ computed_std_skew 4.694855 #> $ computed_std_kurt 23.04167 #> $ ci_lo 0 #> $ ci_hi 0.775"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Beta Parameters — util_beta_param_estimate","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"function automatically scale data 0 1 already. means can pass vector like mtcars$mpg worry . function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated beta data. Three different methods shape parameters supplied: Bayes NIST mme EnvStats mme, see EnvStats::ebeta()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"","code":"util_beta_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Beta Parameters — util_beta_param_estimate","text":".x vector data passed function. Must numeric, values must 0 <= x <= 1 .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"function attempt estimate beta shape1 shape2 parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_beta_param_estimate(x) #> For the beta distribution, its mean 'mu' should be 0 < mu < 1. The data will #> therefore be scaled to enforce this. output$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape1 shape2 shape…¹ #> #> 1 Beta 32 10.4 33.9 0.412 0.0658 Bayes 13.2 18.8 0.702 #> 2 Beta 32 10.4 33.9 0.412 0.0658 NIST_MME 1.11 1.58 0.702 #> 3 Beta 32 10.4 33.9 0.412 0.0658 EnvStats… 1.16 1.65 0.702 #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot() tb <- rbeta(50, 2.5, 1.4) util_beta_param_estimate(tb)$parameter_tbl #> There was no need to scale the data. #> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape1 shape2 shape…¹ #> #> 1 Beta 50 0.101 0.971 0.623 0.0441 Bayes 31.2 18.8 1.66 #> 2 Beta 50 0.101 0.971 0.623 0.0441 NIST_MME 2.70 1.63 1.66 #> 3 Beta 50 0.101 0.971 0.623 0.0441 EnvStats… 2.76 1.67 1.66 #> # … with abbreviated variable name ¹​shape_ratio"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_beta_stats_tbl","title":"Distribution Statistics — util_beta_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_beta_stats_tbl","text":"","code":"util_beta_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_beta_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_beta_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_beta_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_beta_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_beta_stats_tbl","text":"","code":"library(dplyr) tidy_beta() %>% util_beta_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_beta\" #> $ function_call \"Beta c(1, 1, 0)\" #> $ distribution \"Beta\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0.5 #> $ mode \"undefined\" #> $ range \"0 to 1\" #> $ std_dv 0.2886751 #> $ coeff_var 0.5773503 #> $ skewness 0 #> $ kurtosis NA #> $ computed_std_skew -0.4044672 #> $ computed_std_kurt 2.234254 #> $ ci_lo 0.02580016 #> $ ci_hi 0.9298892"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Binomial Parameters — util_binomial_param_estimate","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"function check see given vector .x either numeric vector factor vector least two levels cause error function abort. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated binomial data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"","code":"util_binomial_param_estimate(.x, .size = NULL, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":".x vector data passed function. Must numeric, values must 0 <= x <= 1 .size Number trials, zero . .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"function attempt estimate binomial p_hat size parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"","code":"library(dplyr) library(ggplot2) tb <- rbinom(50, 1, .1) output <- util_binomial_param_estimate(tb) output$parameter_tbl #> # A tibble: 1 × 10 #> dist_type samp_size min max mean variance method prob size shape…¹ #> #> 1 Binomial 50 0 1 0.12 0.108 EnvStats_M… 0.12 50 0.0024 #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_binomial_stats_tbl","title":"Distribution Statistics — util_binomial_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_binomial_stats_tbl","text":"","code":"util_binomial_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_binomial_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_binomial_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_binomial_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_binomial_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_binomial_stats_tbl","text":"","code":"library(dplyr) tidy_binomial() %>% util_binomial_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_binomial\" #> $ function_call \"Binomial c(0, 1)\" #> $ distribution \"Binomial\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ mode_lower 0 #> $ mode_upper 1 #> $ range \"0 to 0\" #> $ std_dv 0 #> $ coeff_var NaN #> $ skewness -Inf #> $ kurtosis NaN #> $ computed_std_skew NaN #> $ computed_std_kurt NaN #> $ ci_lo 0 #> $ ci_hi 0"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Cauchy Parameters — util_cauchy_param_estimate","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated cauchy data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"","code":"util_cauchy_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"function attempt estimate cauchy location scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- tidy_cauchy(.location = 0, .scale = 1)$y output <- util_cauchy_param_estimate(x) output$parameter_tbl #> # A tibble: 1 × 8 #> dist_type samp_size min max method location scale ratio #> #> 1 Cauchy 50 -98.3 20.2 MASS 0.0754 1.59 0.0473 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_cauchy_stats_tbl","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"","code":"util_cauchy_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_cauchy_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"","code":"library(dplyr) tidy_cauchy() %>% util_cauchy_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_cauchy\" #> $ function_call \"Cauchy c(0, 1)\" #> $ distribution \"Cauchy\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean \"undefined\" #> $ median 0 #> $ mode 0 #> $ std_dv \"undefined\" #> $ coeff_var \"undefined\" #> $ skewness 0 #> $ kurtosis \"undefined\" #> $ computed_std_skew 2.338888 #> $ computed_std_kurt 16.64017 #> $ ci_lo -6.451524 #> $ ci_hi 8.968239"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_chisquare_stats_tbl","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"","code":"util_chisquare_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_chisquare_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"","code":"library(dplyr) tidy_chisquare() %>% util_chisquare_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_chisquare\" #> $ function_call \"Chisquare c(1, 1)\" #> $ distribution \"Chisquare\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ median 0.3333333 #> $ mode \"undefined\" #> $ std_dv 1.414214 #> $ coeff_var 1.414214 #> $ skewness 2.828427 #> $ kurtosis 15 #> $ computed_std_skew 1.80429 #> $ computed_std_kurt 6.598183 #> $ ci_lo 0.009104106 #> $ ci_hi 7.089998"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Exponential Parameters — util_exponential_param_estimate","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"function attempt estimate exponential rate parameter given vector values. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated exponential data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"","code":"util_exponential_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":".x vector data passed function. Must numeric. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"function see given vector .x numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"","code":"library(dplyr) library(ggplot2) te <- tidy_exponential(.rate = .1) %>% pull(y) output <- util_exponential_param_estimate(te) output$parameter_tbl #> # A tibble: 1 × 8 #> dist_type samp_size min max mean variance method rate #> #> 1 Exponential 50 0.240 40.7 11.5 121. NIST_MME 0.0870 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_exponential_stats_tbl","title":"Distribution Statistics — util_exponential_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_exponential_stats_tbl","text":"","code":"util_exponential_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_exponential_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_exponential_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_exponential_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_exponential_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_exponential_stats_tbl","text":"","code":"library(dplyr) tidy_exponential() %>% util_exponential_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_exponential\" #> $ function_call \"Exponential c(1)\" #> $ distribution \"Exponential\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ median 0.6931472 #> $ mode 1 #> $ range \"1 to Inf\" #> $ std_dv 1 #> $ coeff_var 1 #> $ skewness 2 #> $ kurtosis 9 #> $ computed_std_skew 3.194111 #> $ computed_std_kurt 16.7398 #> $ ci_lo 0.0273818 #> $ ci_hi 2.733512"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_f_stats_tbl","title":"Distribution Statistics — util_f_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_f_stats_tbl","text":"","code":"util_f_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_f_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_f_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_f_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_f_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_f_stats_tbl","text":"","code":"library(dplyr) tidy_f() %>% util_f_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_f\" #> $ function_call \"F Distribution c(1, 1, 0)\" #> $ distribution \"F\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean \"undefined\" #> $ median \"Not computed\" #> $ mode \"undefined\" #> $ std_dv \"undefined\" #> $ coeff_var \"undefined\" #> $ skewness \"undefined\" #> $ kurtosis \"Not computed\" #> $ computed_std_skew 6.821724 #> $ computed_std_kurt 47.69216 #> $ ci_lo 0.006746585 #> $ ci_hi 97.10469"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Gamma Parameters — util_gamma_param_estimate","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"function attempt estimate gamma shape scale parameters given vector values. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated gamma data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"","code":"util_gamma_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":".x vector data passed function. Must numeric. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"function see given vector .x numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"","code":"library(dplyr) library(ggplot2) tg <- tidy_gamma(.shape = 1, .scale = .3) %>% pull(y) output <- util_gamma_param_estimate(tg) output$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape scale shape…¹ #> #> 1 Gamma 50 0.00810 0.896 0.275 0.233 NIST_MME 1.39 0.198 7.03 #> 2 Gamma 50 0.00810 0.896 0.275 0.233 EnvStats… 1.36 0.198 6.89 #> 3 Gamma 50 0.00810 0.896 0.275 0.233 EnvStats… 1.32 0.198 6.68 #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_gamma_stats_tbl","title":"Distribution Statistics — util_gamma_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_gamma_stats_tbl","text":"","code":"util_gamma_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_gamma_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_gamma_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_gamma_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_gamma_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_gamma_stats_tbl","text":"","code":"library(dplyr) tidy_gamma() %>% util_gamma_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_gamma\" #> $ function_call \"Gamma c(1, 0.3)\" #> $ distribution \"Gamma\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ mode 0 #> $ range \"0 to Inf\" #> $ std_dv 1 #> $ coeff_var 1 #> $ skewness 2 #> $ kurtosis 9 #> $ computed_std_skew 1.997294 #> $ computed_std_kurt 7.785293 #> $ ci_lo 0.01357778 #> $ ci_hi 0.805893"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Geometric Parameters — util_geometric_param_estimate","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"function attempt estimate geometric prob parameter given vector values .x. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated geometric data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"","code":"util_geometric_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":".x vector data passed function. Must non-negative integers. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"function see given vector .x numeric vector. attempt estimate prob parameter geometric distribution.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"","code":"library(dplyr) library(ggplot2) tg <- tidy_geometric(.prob = .1) %>% pull(y) output <- util_geometric_param_estimate(tg) output$parameter_tbl #> # A tibble: 2 × 9 #> dist_type samp_size min max mean variance sum_x method shape #> #> 1 Geometric 50 0 39 9.32 65.7 466 EnvStats_MME 0.0969 #> 2 Geometric 50 0 39 9.32 65.7 466 EnvStats_MVUE 0.0951 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_geometric_stats_tbl","title":"Distribution Statistics — util_geometric_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_geometric_stats_tbl","text":"","code":"util_geometric_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_geometric_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_geometric_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_geometric_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_geometric_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_geometric_stats_tbl","text":"","code":"library(dplyr) tidy_geometric() %>% util_geometric_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_geometric\" #> $ function_call \"Geometric c(1)\" #> $ distribution \"Geometric\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ mode 0 #> $ range \"0 to Inf\" #> $ std_dv 0 #> $ coeff_var 0 #> $ skewness Inf #> $ kurtosis Inf #> $ computed_std_skew NaN #> $ computed_std_kurt NaN #> $ ci_lo 0 #> $ ci_hi 0"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"function attempt estimate geometric prob parameter given vector values .x. Estimate m, number white balls urn, m+n, total number balls urn, hypergeometric distribution.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"","code":"util_hypergeometric_param_estimate( .x, .m = NULL, .total = NULL, .k, .auto_gen_empirical = TRUE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":".x non-negative integer indicating number white balls sample size .k drawn without replacement urn. missing, undefined infinite values. .m Non-negative integer indicating number white balls urn. must supply .m .total, . missing values. .total positive integer indicating total number balls urn (.e., m+n). must supply .m .total, . missing values. .k positive integer indicating number balls drawn without replacement urn. missing values. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"function see given vector .x numeric integer. attempt estimate prob parameter geometric distribution. Missing (NA), undefined (NaN), infinite (Inf, -Inf) values allowed. Let .x observation hypergeometric distribution parameters .m = M, .n = N, .k = K. R nomenclature, .x represents number white balls drawn sample .k balls drawn without replacement urn containing .m white balls .n black balls. total number balls urn thus .m + .n. Denote total number balls T = .m + .n","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"","code":"library(dplyr) library(ggplot2) th <- rhyper(10, 20, 30, 5) output <- util_hypergeometric_param_estimate(th, .total = 50, .k = 5) output$parameter_tbl #> # A tibble: 2 × 5 #> dist_type samp_size method m total #> #> 1 Hypergeometric 10 EnvStats_MLE 30.6 NA #> 2 Hypergeometric 10 EnvStats_MVUE 30 50 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_hypergeometric_stats_tbl","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"","code":"util_hypergeometric_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"","code":"library(dplyr) tidy_hypergeometric() %>% util_hypergeometric_stats_tbl() %>% glimpse() #> Warning: NaNs produced #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_hypergeometric\" #> $ function_call \"Hypergeometric c(0, 0, 0)\" #> $ distribution \"Hypergeometric\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean NaN #> $ mode_lower -0.5 #> $ mode_upper 0.5 #> $ range \"0 to Inf\" #> $ std_dv NaN #> $ coeff_var NaN #> $ skewness NaN #> $ kurtosis NaN #> $ computed_std_skew NaN #> $ computed_std_kurt NaN #> $ ci_lo 0 #> $ ci_hi 0"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Logistic Parameters — util_logistic_param_estimate","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated logistic data. Three different methods shape parameters supplied: MLE MME MMUE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"","code":"util_logistic_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"function attempt estimate logistic location scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_logistic_param_estimate(x) output$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean basic_scale method locat…¹ scale shape…² #> #> 1 Logistic 32 10.4 33.9 20.1 3.27 EnvSt… 20.1 3.27 6.14 #> 2 Logistic 32 10.4 33.9 20.1 3.27 EnvSt… 20.1 3.32 6.05 #> 3 Logistic 32 10.4 33.9 20.1 3.27 EnvSt… 20.1 12.6 1.60 #> # … with abbreviated variable names ¹​location, ²​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot() t <- rlogis(50, 2.5, 1.4) util_logistic_param_estimate(t)$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean basic_scale method locat…¹ scale shape…² #> #> 1 Logistic 50 -5.04 7.41 2.23 1.41 EnvSt… 2.23 1.41 1.58 #> 2 Logistic 50 -5.04 7.41 2.23 1.41 EnvSt… 2.23 1.43 1.56 #> 3 Logistic 50 -5.04 7.41 2.23 1.41 EnvSt… 2.23 1.65 1.35 #> # … with abbreviated variable names ¹​location, ²​shape_ratio"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_logistic_stats_tbl","title":"Distribution Statistics — util_logistic_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_logistic_stats_tbl","text":"","code":"util_logistic_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_logistic_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_logistic_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_logistic_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_logistic_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_logistic_stats_tbl","text":"","code":"library(dplyr) tidy_logistic() %>% util_logistic_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_logistic\" #> $ function_call \"Logistic c(0, 1)\" #> $ distribution \"Logistic\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ mode_lower 0 #> $ range \"0 to Inf\" #> $ std_dv 1.813799 #> $ coeff_var 3.289868 #> $ skewness 0 #> $ kurtosis 1.2 #> $ computed_std_skew 0.4760057 #> $ computed_std_kurt 3.253218 #> $ ci_lo -2.845881 #> $ ci_hi 4.53937"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Lognormal Parameters — util_lognormal_param_estimate","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated lognormal data. Three different methods shape parameters supplied: mme, see EnvStats::elnorm() mle, see EnvStats::elnorm()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"","code":"util_lognormal_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"function attempt estimate lognormal meanlog log sd parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_lognormal_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mean_log sd_log shape_ratio #> #> 1 Lognormal 32 10.4 33.9 EnvStats_MVUE 2.96 0.298 9.93 #> 2 Lognormal 32 10.4 33.9 EnvStats_MME 2.96 0.293 10.1 output$combined_data_tbl %>% tidy_combined_autoplot() tb <- tidy_lognormal(.meanlog = 2, .sdlog = 1) %>% pull(y) util_lognormal_param_estimate(tb)$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mean_log sd_log shape_ratio #> #> 1 Lognormal 50 0.721 97.7 EnvStats_MVUE 1.84 1.13 1.64 #> 2 Lognormal 50 0.721 97.7 EnvStats_MME 1.84 1.12 1.65"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_lognormal_stats_tbl","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"","code":"util_lognormal_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_lognormal_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"","code":"library(dplyr) tidy_lognormal() %>% util_lognormal_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_lognormal\" #> $ function_call \"Lognormal c(0, 1)\" #> $ distribution \"Lognormal\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1.648721 #> $ median 1 #> $ mode 0.3678794 #> $ range \"0 to Inf\" #> $ std_dv 2.161197 #> $ coeff_var 1.310832 #> $ skewness 6.184877 #> $ kurtosis 113.9364 #> $ computed_std_skew 1.816789 #> $ computed_std_kurt 5.833297 #> $ ci_lo 0.1131009 #> $ ci_hi 5.867792"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated negative binomial data. Two different methods shape parameters supplied: MLE/MME MMUE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"","code":"util_negative_binomial_param_estimate(.x, .size, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":".x vector data passed function. .size size parameter. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"function attempt estimate negative binomial size prob parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- as.integer(mtcars$mpg) output <- util_negative_binomial_param_estimate(x, .size = 1) output$parameter_tbl #> # A tibble: 2 × 9 #> dist_type samp_size min max mean method size prob shape…¹ #> #> 1 Negative Binomial 32 10 33 19.7 EnvStats_M… 32 0.0483 662 #> 2 Negative Binomial 32 10 33 19.7 EnvStats_M… 32 0.0469 682. #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot() t <- rnbinom(50, 1, .1) util_negative_binomial_param_estimate(t, .size = 1)$parameter_tbl #> # A tibble: 2 × 9 #> dist_type samp_size min max mean method size prob shape…¹ #> #> 1 Negative Binomial 50 0 26 8.7 EnvStats_MM… 50 0.103 485 #> 2 Negative Binomial 50 0 26 8.7 EnvStats_MM… 50 0.101 494. #> # … with abbreviated variable name ¹​shape_ratio"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_negative_binomial_stats_tbl","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"","code":"util_negative_binomial_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"","code":"library(dplyr) tidy_negative_binomial() %>% util_negative_binomial_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_negative_binomial\" #> $ function_call \"Negative Binomial c(1, 0.1)\" #> $ distribution \"Negative_binomial\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 0.1111111 #> $ mode_lower 0 #> $ range \"0 to Inf\" #> $ std_dv 0.3513642 #> $ coeff_var 0.1234568 #> $ skewness 3.478505 #> $ kurtosis 14.1 #> $ computed_std_skew 1.244179 #> $ computed_std_kurt 4.68958 #> $ ci_lo 0 #> $ ci_hi 26.75"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated normal data. Three different methods shape parameters supplied: MLE/MME MVUE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"","code":"util_normal_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"function attempt estimate normal gaussian mean standard deviation parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_normal_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mu stan_dev shape_ratio #> #> 1 Gaussian 32 10.4 33.9 EnvStats_MME_MLE 20.1 5.93 3.39 #> 2 Gaussian 32 10.4 33.9 EnvStats_MVUE 20.1 6.03 3.33 output$combined_data_tbl %>% tidy_combined_autoplot() t <- rnorm(50, 0, 1) util_normal_param_estimate(t)$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mu stan_dev shape_ratio #> #> 1 Gaussian 50 -1.94 2.54 EnvStats_MME_MLE 0.105 0.959 0.109 #> 2 Gaussian 50 -1.94 2.54 EnvStats_MVUE 0.105 0.968 0.108"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_normal_stats_tbl","title":"Distribution Statistics — util_normal_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_normal_stats_tbl","text":"","code":"util_normal_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_normal_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_normal_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_normal_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_normal_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_normal_stats_tbl","text":"","code":"library(dplyr) tidy_normal() %>% util_normal_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_gaussian\" #> $ function_call \"Gaussian c(0, 1)\" #> $ distribution \"Gaussian\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ median 0.1488648 #> $ mode 0 #> $ std_dv 1 #> $ coeff_var Inf #> $ skewness 0 #> $ kurtosis 3 #> $ computed_std_skew -0.3345225 #> $ computed_std_kurt 2.859214 #> $ ci_lo -2.083379 #> $ ci_hi 1.850531"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Pareto Parameters — util_pareto_param_estimate","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated pareto data. Two different methods shape parameters supplied: LSE MLE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"","code":"util_pareto_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"function attempt estimate pareto shape scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_pareto_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method shape scale shape_ratio #> #> 1 Pareto 32 10.4 33.9 LSE 13.7 2.86 4.79 #> 2 Pareto 32 10.4 33.9 MLE 10.4 1.62 6.40 output$combined_data_tbl %>% tidy_combined_autoplot() t <- tidy_pareto(50, 1, 1) %>% pull(y) util_pareto_param_estimate(t)$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method shape scale shape_ratio #> #> 1 Pareto 50 0.00883 60.5 LSE 0.0764 0.402 0.190 #> 2 Pareto 50 0.00883 60.5 MLE 0.00883 0.217 0.0407"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_pareto_stats_tbl","title":"Distribution Statistics — util_pareto_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_pareto_stats_tbl","text":"","code":"util_pareto_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_pareto_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_pareto_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_pareto_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_pareto_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_pareto_stats_tbl","text":"","code":"library(dplyr) tidy_pareto() %>% util_pareto_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_pareto\" #> $ function_call \"Pareto c(10, 0.1)\" #> $ distribution \"Pareto\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0.1111111 #> $ mode_lower 0.1 #> $ range \"0 to Inf\" #> $ std_dv 0.0124226 #> $ coeff_var 0.000154321 #> $ skewness 2.811057 #> $ kurtosis 14.82857 #> $ computed_std_skew 1.309907 #> $ computed_std_kurt 4.325999 #> $ ci_lo 0.0002655451 #> $ ci_hi 0.02473998"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Poisson Parameters — util_poisson_param_estimate","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated poisson data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"","code":"util_poisson_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"function attempt estimate pareto lambda parameter given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- as.integer(mtcars$mpg) output <- util_poisson_param_estimate(x) output$parameter_tbl #> # A tibble: 1 × 6 #> dist_type samp_size min max method lambda #> #> 1 Posson 32 10 33 MLE 19.7 output$combined_data_tbl %>% tidy_combined_autoplot() t <- rpois(50, 5) util_poisson_param_estimate(t)$parameter_tbl #> # A tibble: 1 × 6 #> dist_type samp_size min max method lambda #> #> 1 Posson 50 1 12 MLE 5"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_poisson_stats_tbl","title":"Distribution Statistics — util_poisson_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_poisson_stats_tbl","text":"","code":"util_poisson_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_poisson_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_poisson_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_poisson_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_poisson_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_poisson_stats_tbl","text":"","code":"library(dplyr) tidy_poisson() %>% util_poisson_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_poisson\" #> $ function_call \"Poisson c(1)\" #> $ distribution \"Poisson\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ mode 1 #> $ range \"0 to Inf\" #> $ std_dv 1 #> $ coeff_var 1 #> $ skewness 1 #> $ kurtosis 4 #> $ computed_std_skew 0.9399507 #> $ computed_std_kurt 3.280704 #> $ ci_lo 0 #> $ ci_hi 3"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_t_stats_tbl","title":"Distribution Statistics — util_t_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_t_stats_tbl","text":"","code":"util_t_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_t_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_t_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_t_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_t_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_t_stats_tbl","text":"","code":"library(dplyr) tidy_t() %>% util_t_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_t\" #> $ function_call \"T Distribution c(1, 0)\" #> $ distribution \"T\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ median 0 #> $ mode 0 #> $ std_dv \"undefined\" #> $ coeff_var \"undefined\" #> $ skewness 0 #> $ kurtosis \"undefined\" #> $ computed_std_skew -6.267111 #> $ computed_std_kurt 42.42918 #> $ ci_lo -20.13772 #> $ ci_hi 5.176328"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Uniform Parameters — util_uniform_param_estimate","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated uniform data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"","code":"util_uniform_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"function attempt estimate uniform min max parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- tidy_uniform(.min = 1, .max = 3)$y output <- util_uniform_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method min_est max_est ratio #> #> 1 Uniform 50 1.04 2.81 NIST_MME 1.02 2.78 0.366 #> 2 Uniform 50 1.04 2.81 NIST_MLE 1 3 0.333 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_uniform_stats_tbl","title":"Distribution Statistics — util_uniform_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_uniform_stats_tbl","text":"","code":"util_uniform_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_uniform_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_uniform_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_uniform_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_uniform_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_uniform_stats_tbl","text":"","code":"library(dplyr) tidy_uniform() %>% util_uniform_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 16 #> $ tidy_function \"tidy_uniform\" #> $ function_call \"Uniform c(0, 1)\" #> $ distribution \"Uniform\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0.5 #> $ median 0.5 #> $ std_dv 0.2886751 #> $ coeff_var 0.5773503 #> $ skewness 0 #> $ kurtosis 1.8 #> $ computed_std_skew -0.4269857 #> $ computed_std_kurt 2.328649 #> $ ci_lo 0.04275606 #> $ ci_hi 0.9214472"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Weibull Parameters — util_weibull_param_estimate","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated weibull data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"","code":"util_weibull_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"function attempt estimate weibull shape scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- tidy_weibull(.shape = 1, .scale = 2)$y output <- util_weibull_param_estimate(x) output$parameter_tbl #> # A tibble: 1 × 8 #> dist_type samp_size min max method shape scale shape_ratio #> #> 1 Weibull 50 0.0411 6.99 NIST 1.10 2.19 0.504 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_weibull_stats_tbl","title":"Distribution Statistics — util_weibull_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_weibull_stats_tbl","text":"","code":"util_weibull_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_weibull_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_weibull_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_weibull_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_weibull_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_weibull_stats_tbl","text":"","code":"library(dplyr) tidy_weibull() %>% util_weibull_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 16 #> $ tidy_function \"tidy_weibull\" #> $ function_call \"Weibull c(1, 1)\" #> $ distribution \"Weibull\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1.256003 #> $ median 1.134406 #> $ mode 0 #> $ range \"0 to Inf\" #> $ std_dv 1.166261 #> $ coeff_var 1.360165 #> $ computed_std_skew 1.185473 #> $ computed_std_kurt 4.728838 #> $ ci_lo 0.05001485 #> $ ci_hi 3.80199"},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-development-version","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity (development version)","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-development-version","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity (development version)","text":"Fix #302 - Add function tidy_bernoulli() Fix #304 - Add function util_bernoulli_param_estimate() Fix #305 - Add function util_bernoulli_stats_tbl()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-development-version","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity (development version)","text":"Fix #291 - Update tidy_stat_tbl() fix tibble output longer ignores passed arguments fix data.table directly pass … arguments. Fix #295 - Drop warning message passing arguments .use_data_table = TRUE Fix #303 - Add tidy_bernoulli() autoplot. Fix #299 - Update tidy_stat_tbl() Fix #309 - Add function internal use drop dependency stringr. Function dist_type_extractor() used several functions library. Fix #310 - Update combine-multi-dist use dist_type_extractor()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-123","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.2.3","title":"TidyDensity 1.2.3","text":"CRAN release: 2022-10-04","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-2-3","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.2.3","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-2-3","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.2.3","text":"Fix #237 - Add function bootstrap_density_augment() Fix #238 - Add functions bootstrap_p_vec() bootstrap_p_augment() Fix #239 - Add functions bootstrap_q_vec() bootstrap_q_augment() Fix #256 #257 #258 #260 #265 #266 #267 #268 - Add functions cmean() chmean() cgmean() cmedian() csd() ckurtosis() cskewness() cvar() Fix #250 - Add function bootstrap_stat_plot() Fix #276 - Add function tidy_stat_tbl() Fix #281 adds parameter .user_data_table set FALSE default. set TRUE use [data.table::melt()] underlying work speeding output benchmark test regular tibble 72 seconds data.table. 15 seconds.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-2-3","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.2.3","text":"Fix #242 - Fix prop check tidy_bootstrap() Fix #247 - Add attributes bootstrap_density_augment() output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-122","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.2.2","title":"TidyDensity 1.2.2","text":"CRAN release: 2022-08-10","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-2-2","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.2.2","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-2-2","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.2.2","text":"Fix #229 - Add tidy_normal() list tested distributions. Add AIC linear model metric, add stats::ks.test() metric.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-2-2","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.2.2","text":"Fix #228 - Add ks.test distribution comparison. Fix #227 - Add AIC normal distribution comparison.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-121","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.2.1","title":"TidyDensity 1.2.1","text":"CRAN release: 2022-07-19","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-2-1","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.2.1","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-2-1","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.2.1","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvments-1-2-1","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvments","title":"TidyDensity 1.2.1","text":"Fix #210 - Fix param_grid order internal affected attributes thus display order parameters. Fix #211 - Add High Low CI tidy_distribution_summary_tbl() Fix #213 - Use purrr::compact() list distributions passed order prevent issue occurring #212 Fix #212 - Make tidy_distribution_comparison() robust terms handling bad erroneous data. Fix #216 - Add attribute “tibble_type” tidy_multi_single_dist() helps work functions like tidy_random_walk()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-120","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.2.0","title":"TidyDensity 1.2.0","text":"CRAN release: 2022-06-08","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-2-0","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.2.0","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-2-0","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.2.0","text":"Fix #181 - Add functions color_blind() td_scale_fill_colorblind() td_scale_color_colorblind() Fix #187 - Add functions ci_lo() ci_hi() Fix #189 - Add function tidy_bootstrap() Fix #190 - Add function bootstrap_unnest_tbl() Fix #202 - Add function tidy_distribution_comparison()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-2-0","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.2.0","text":"Fix #176 - Update _autoplot functions include cumulative mean MCMC chart taking advantage .num_sims parameter tidy_ distribution functions. Fix #184 - Update tidy_empirical() add parameter .distribution_type Fix #183 - tidy_empirical() now plotted _autoplot functions. Fix #188 - Add .num_sims parameter tidy_empirical() Fix #196 - Add ci_lo() ci_hi() stats tbl functions. Fix #201 - Correct attribute distribution_family_type discrete tidy_geometric()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-110","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.1.0","title":"TidyDensity 1.1.0","text":"CRAN release: 2022-05-06","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-1-0","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.1.0","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-1-0","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.1.0","text":"Fix #119 - Add function tidy_four_autoplot() - auto plot density, qq, quantile probability plots single graph. Fix #125 - Add function util_weibull_param_estimate() Fix #126 - Add function util_uniform_param_estimate() Fix #127 - Add function util_cauchy_param_estimate() Fix #130 - Add function tidy_t() - Also add plotting functions. Fix #151 - Add function tidy_mixture_density() Fix #150 - Add function util_geometric_stats_tbl() Fix #149 - Add function util_hypergeometric_stats_tbl() Fix #148 - Add function util_logistic_stats_tbl() Fix #147 - Add function util_lognormal_stats_tbl() Fix #146 - Add function util_negative_binomial_stats_tbl() Fix #145 - Add function util_normal_stats_tbl() Fix #144 - Add function util_pareto_stats_tbl() Fix #143 - Add function util_poisson_stats_tbl() Fix #142 - Add function util_uniform_stats_tbl() Fix #141 - Add function util_cauchy_stats_tbl() Fix #140 - Add function util_t_stats_tbl() Fix #139 - Add function util_f_stats_tbl() Fix #138 - Add function util_chisquare_stats_tbl() Fix #137 - Add function util_weibull_stats_tbl() Fix #136 - Add function util_gamma_stats_tbl() Fix #135 - Add function util_exponential_stats_tbl() Fix #134 - Add function util_binomial_stats_tbl() Fix #133 - Add function util_beta_stats_tbl()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-1-0","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.1.0","text":"Fix #110 - Bug fix, correct p calculation tidy_poisson() now produce correct probability chart auto plot functions. Fix #112 - Bug fix, correct p calculation tidy_hypergeometric() produce correct probability chart auto plot functions. Fix #115 - Fix spelling Quantile chart. Fix #117 - Fix probability plot x axis label. Fix #118 - Fix fill color combined auto plot Fix #122 - tidy_distribution_summary_tbl() function take output tidy_multi_single_dist() Fix #166 - Change plotting functions ggplot2::xlim(0, max_dy) ggplot2::ylim(0, max_dy) Fix #169 - Fix computation q column Fix #170 - Fix graphing quantile chart due #169","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-101","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.0.1","title":"TidyDensity 1.0.1","text":"CRAN release: 2022-03-27","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-0-1","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.0.1","text":"Fix #91 - Bug fix, change tidy_gamma() parameter .rate .scale Fixtidy_autoplot_functions incorporate change. Fixutil_gamma_param_estimate()sayscaleinstead ofrate` returned estimated parameters.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-0-1","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.0.1","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-0-1","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.0.1","text":"Fix #90 - Make sure .geom_smooth set TRUE ggplot2::xlim(0, max_dy) set. Fix #100 - tidy_multi_single_dist() failed distribution single parameter like tidy_poisson() Fix #96 - Enhance tidy_ distribution functions add attribute either discrete continuous helps autoplot process. Fix #97 - Enhance tidy_autoplot() use histogram lines density plot depending distribution discrete continuous. Fix #99 - Enhance tidy_multi_dist_autoplot() use histogram lines density plot depending distribution discrete continuous.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-100","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.0.0","title":"TidyDensity 1.0.0","text":"CRAN release: 2022-03-08","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-0-0","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.0.0","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-0-0","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.0.0","text":"Fix #27 - Add function tidy_binomial() Fix #32 - Add function tidy_geometric() Fix #33 - Add function tidy_negative_binomial() Fix #34 - Add function tidy_zero_truncated_poisson() Fix #35 - Add function tidy_zero_truncated_geometric() Fix #36 - Add function tidy_zero_truncated_binomial() Fix #37 - Add function tidy_zero_truncated_negative_binomial() Fix #41 - Add function tidy_pareto1() Fix #42 - Add function tidy_pareto() Fix #43 - Add function tidy_inverse_pareto() Fix #58 - Add function tidy_random_walk() Fix #60 - Add function tidy_random_walk_autoplot() Fix #47 - Add function tidy_generalized_pareto() Fix #44 - Add function tidy_paralogistic() Fix #38 - Add function tidy_inverse_exponential() Fix #45 - Add function tidy_inverse_gamma() Fix #46 - Add function tidy_inverse_weibull() Fix #48 - Add function tidy_burr() Fix #49 - Add function tidy_inverse_burr() Fix #50 - Add function tidy_inverse_normal() Fix #51 - Add function tidy_generalized_beta() Fix #26 - Add function tidy_multi_single_dist() Fix #62 - Add function tidy_multi_dist_autoplot() Fix #66 - Add function tidy_combine_distributions() Fix #69 - Add functions tidy_kurtosis_vec(), tidy_skewness_vec(), tidy_range_statistic() Fix #75 - Add function util_beta_param_estimate() Fix #76 - Add function util_binomial_param_estimate() Fix #77 - Add function util_exponential_param_estimate() Fix #78 - Add function util_gamma_param_estimate() Fix #79 - Add function util_geometric_param_estimate() Fix #80 - Add function util_hypergeometric_param_estimate() Fix #81 - Add function util_lognormal_param_estimate() Fix #89 - Add function tidy_scale_zero_one_vec() Fix #87 - Add function tidy_combined_autoplot() Fix #82 - Add function util_logistic_param_estimate() Fix #83 - Add function util_negative_binomial_param_estimate() Fix #84 - Add function util_normal_param_estimate() Fix #85 - Add function util_pareto_param_estimate() Fix #86 - Add function util_poisson_param_estimate()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"fixes-and-minor-improvements-1-0-0","dir":"Changelog","previous_headings":"","what":"Fixes and Minor Improvements","title":"TidyDensity 1.0.0","text":"Fix #30 - Move crayon, rstudioapi, cli Suggests Imports due pillar longer importing. Fix #52 - Add parameter .geom_rug tidy_autoplot() function Fix #54 - Add parameter .geom_point tidy_autoplot() function Fix #53 - Add parameter .geom_smooth tidy_autoplot() function Fix #55 - Add parameter .geom_jitter tidy_autoplot() function Fix #57 - Fix tidy_autoplot() distribution tidy_empirical() legend argument fail. Fix #56 - Add attributes .n .num_sims (1L now) tidy_empirical() Fix #61 - Update _pkgdown.yml file update site. Fix #67 - Add param_grid, param_grid_txt, dist_with_params attributes tidy_ distribution functions. Fix #70 - Add ... grouping parameter tidy_distribution_summary_tbl() Fix #88 - Make column dist_type factor tidy_combine_distributions()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-001","dir":"Changelog","previous_headings":"","what":"TidyDensity 0.0.1","title":"TidyDensity 0.0.1","text":"CRAN release: 2022-01-21","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-0-0-1","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 0.0.1","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-0-0-1","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 0.0.1","text":"Fix #1 - Add function tidy_normal() Fix #4 - Add function tidy_gamma() Fix #5 - Add function tidy_beta() Fix #6 - Add function tidy_poisson() Fix #2 - Add function tidy_autoplot() Fix #11 - Add function tidy_distribution_summary_tbl() Fix #10 - Add function tidy_empirical() Fix #13 - Add function tidy_uniform() Fix #14 - Add function tidy_exponential() Fix #15 - Add function tidy_logistic() Fix #16 - Add function tidy_lognormal() Fix #17 - Add function tidy_weibull() Fix #18 - Add function tidy_chisquare() Fix #19 - Add function tidy_cauchy() Fix #20 - Add function tidy_hypergeometric() Fix #21 - Add function tidy_f()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-0-0-1","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 0.0.1","text":"None","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-0-0-0-9000","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 0.0.0.9000","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-0-0-0-9000","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 0.0.0.9000","text":"Added NEWS.md file track changes package.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"fixes-and-minor-improvements-0-0-0-9000","dir":"Changelog","previous_headings":"","what":"Fixes and Minor Improvements","title":"TidyDensity 0.0.0.9000","text":"None","code":""}] +[{"path":"https://www.spsanderson.com/TidyDensity/articles/getting-started.html","id":"example","dir":"Articles","previous_headings":"","what":"Example","title":"Getting Started with TidyDensity","text":"basic example shows easy generate data TidyDensity: example plot tidy_normal data. can also take look plots number simulations greater nine. automatically turn legend become noisy.","code":"library(TidyDensity) library(dplyr) library(ggplot2) tidy_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 -0.883 -3.47 0.000214 0.189 -0.883 #> 2 1 2 -1.62 -3.31 0.000612 0.0523 -1.62 #> 3 1 3 -0.181 -3.16 0.00153 0.428 -0.181 #> 4 1 4 0.549 -3.00 0.00337 0.709 0.549 #> 5 1 5 -0.109 -2.84 0.00657 0.456 -0.109 #> 6 1 6 -0.446 -2.69 0.0114 0.328 -0.446 #> 7 1 7 1.08 -2.53 0.0179 0.859 1.08 #> 8 1 8 -0.758 -2.37 0.0257 0.224 -0.758 #> 9 1 9 0.262 -2.21 0.0344 0.603 0.262 #> 10 1 10 0.516 -2.06 0.0436 0.697 0.516 #> # … with 40 more rows tn <- tidy_normal(.n = 100, .num_sims = 6) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\") tn <- tidy_normal(.n = 100, .num_sims = 20) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Steven Sanderson. Author, maintainer. Steven Sanderson. Copyright holder.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Sanderson S (2022). TidyDensity: Functions Tidy Analysis Generation Random Data. R package version 1.2.3.9000, https://github.com/spsanderson/TidyDensity.","code":"@Manual{, title = {TidyDensity: Functions for Tidy Analysis and Generation of Random Data}, author = {Steven Sanderson}, year = {2022}, note = {R package version 1.2.3.9000}, url = {https://github.com/spsanderson/TidyDensity}, }"},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"our-pledge","dir":"","previous_headings":"","what":"Our Pledge","title":"Contributor Covenant Code of Conduct","text":"members, contributors, leaders pledge make participation community harassment-free experience everyone, regardless age, body size, visible invisible disability, ethnicity, sex characteristics, gender identity expression, level experience, education, socio-economic status, nationality, personal appearance, race, religion, sexual identity orientation. pledge act interact ways contribute open, welcoming, diverse, inclusive, healthy community.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"our-standards","dir":"","previous_headings":"","what":"Our Standards","title":"Contributor Covenant Code of Conduct","text":"Examples behavior contributes positive environment community include: Demonstrating empathy kindness toward people respectful differing opinions, viewpoints, experiences Giving gracefully accepting constructive feedback Accepting responsibility apologizing affected mistakes, learning experience Focusing best just us individuals, overall community Examples unacceptable behavior include: use sexualized language imagery, sexual attention advances kind Trolling, insulting derogatory comments, personal political attacks Public private harassment Publishing others’ private information, physical email address, without explicit permission conduct reasonably considered inappropriate professional setting","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"enforcement-responsibilities","dir":"","previous_headings":"","what":"Enforcement Responsibilities","title":"Contributor Covenant Code of Conduct","text":"Community leaders responsible clarifying enforcing standards acceptable behavior take appropriate fair corrective action response behavior deem inappropriate, threatening, offensive, harmful. Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement spsanderson@gmail.com. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"id_1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"id_2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. Violating terms may lead temporary permanent ban.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"id_3-temporary-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"3. Temporary Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: serious violation community standards, including sustained inappropriate behavior. Consequence: temporary ban sort interaction public communication community specified period time. public private interaction people involved, including unsolicited interaction enforcing Code Conduct, allowed period. Violating terms may lead permanent ban.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"id_4-permanent-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"4. Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.0, available https://www.contributor-covenant.org/version/2/0/code_of_conduct.html. Community Impact Guidelines inspired Mozilla’s code conduct enforcement ladder. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https://www.contributor-covenant.org/translations.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/index.html","id":"tidydensity-","dir":"","previous_headings":"","what":"Functions for Tidy Analysis and Generation of Random Data","title":"Functions for Tidy Analysis and Generation of Random Data","text":"goal TidyDensity make working random numbers different distributions easy. tidy_ distribution functions provide following components: [r_] [d_] [q_] [p_]","code":""},{"path":"https://www.spsanderson.com/TidyDensity/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Functions for Tidy Analysis and Generation of Random Data","text":"can install released version TidyDensity CRAN : development version GitHub :","code":"install.packages(\"TidyDensity\") # install.packages(\"devtools\") devtools::install_github(\"spsanderson/TidyDensity\")"},{"path":"https://www.spsanderson.com/TidyDensity/index.html","id":"example","dir":"","previous_headings":"","what":"Example","title":"Functions for Tidy Analysis and Generation of Random Data","text":"basic example shows solve common problem: example plot tidy_normal data. can also take look plots number simulations greater nine. automatically turn legend become noisy.","code":"library(TidyDensity) library(dplyr) library(ggplot2) tidy_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 2.01 -2.88 0.000255 0.5 Inf #> 2 1 2 -0.636 -2.76 0.000670 0.508 -0.512 #> 3 1 3 -0.317 -2.64 0.00159 0.516 -0.284 #> 4 1 4 -0.319 -2.51 0.00339 0.524 -0.285 #> 5 1 5 1.01 -2.39 0.00661 0.533 0.631 #> 6 1 6 -0.0143 -2.27 0.0118 0.541 -0.0809 #> 7 1 7 -0.431 -2.15 0.0197 0.549 -0.363 #> 8 1 8 0.430 -2.03 0.0309 0.557 0.214 #> 9 1 9 0.504 -1.90 0.0464 0.565 0.264 #> 10 1 10 -1.18 -1.78 0.0675 0.573 -0.993 #> # … with 40 more rows tn <- tidy_normal(.n = 100, .num_sims = 6) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\") tn <- tidy_normal(.n = 100, .num_sims = 20) tidy_autoplot(tn, .plot_type = \"density\") tidy_autoplot(tn, .plot_type = \"quantile\") tidy_autoplot(tn, .plot_type = \"probability\") tidy_autoplot(tn, .plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2022 Steven Paul Sandeson II, MPH Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_density_augment.html","id":null,"dir":"Reference","previous_headings":"","what":"Bootstrap Density Tibble — bootstrap_density_augment","title":"Bootstrap Density Tibble — bootstrap_density_augment","text":"Add density information output tidy_bootstrap(), bootstrap_unnest_tbl().","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_density_augment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bootstrap Density Tibble — bootstrap_density_augment","text":"","code":"bootstrap_density_augment(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_density_augment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Bootstrap Density Tibble — bootstrap_density_augment","text":".data data passed tidy_bootstrap() bootstrap_unnest_tbl() functions.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_density_augment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Bootstrap Density Tibble — bootstrap_density_augment","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_density_augment.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Bootstrap Density Tibble — bootstrap_density_augment","text":"function takes input output tidy_bootstrap() bootstrap_unnest_tbl() returns augmented tibble following columns added : x, y, dx, dy. looks attribute comes using tidy_bootstrap() bootstrap_unnest_tbl() work unless data comes one functions.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_density_augment.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Bootstrap Density Tibble — bootstrap_density_augment","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_density_augment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bootstrap Density Tibble — bootstrap_density_augment","text":"","code":"x <- mtcars$mpg tidy_bootstrap(x) %>% bootstrap_density_augment() #> # A tibble: 50,000 × 5 #> sim_number x y dx dy #> #> 1 1 1 21.4 6.91 0.000155 #> 2 1 2 17.8 8.18 0.00223 #> 3 1 3 30.4 9.45 0.00981 #> 4 1 4 22.8 10.7 0.0134 #> 5 1 5 10.4 12.0 0.00841 #> 6 1 6 21.4 13.3 0.0188 #> 7 1 7 21.4 14.5 0.0410 #> 8 1 8 15.5 15.8 0.0473 #> 9 1 9 22.8 17.1 0.0535 #> 10 1 10 16.4 18.3 0.0682 #> # … with 49,990 more rows tidy_bootstrap(x) %>% bootstrap_unnest_tbl() %>% bootstrap_density_augment() #> # A tibble: 50,000 × 5 #> sim_number x y dx dy #> #> 1 1 1 24.4 2.49 0.000138 #> 2 1 2 17.8 3.98 0.000650 #> 3 1 3 16.4 5.47 0.00227 #> 4 1 4 14.7 6.96 0.00601 #> 5 1 5 13.3 8.46 0.0127 #> 6 1 6 26 9.95 0.0230 #> 7 1 7 30.4 11.4 0.0382 #> 8 1 8 15.5 12.9 0.0575 #> 9 1 9 17.3 14.4 0.0741 #> 10 1 10 15.2 15.9 0.0785 #> # … with 49,990 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_augment.html","id":null,"dir":"Reference","previous_headings":"","what":"Augment Bootstrap P — bootstrap_p_augment","title":"Augment Bootstrap P — bootstrap_p_augment","text":"Takes numeric vector return ecdf probability.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_augment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Augment Bootstrap P — bootstrap_p_augment","text":"","code":"bootstrap_p_augment(.data, .value, .names = \"auto\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_augment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Augment Bootstrap P — bootstrap_p_augment","text":".data data passed augmented function. .value passed rlang::enquo() capture vectors want augment. .names default \"auto\"","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_augment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Augment Bootstrap P — bootstrap_p_augment","text":"augmented tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_augment.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Augment Bootstrap P — bootstrap_p_augment","text":"Takes numeric vector return ecdf probability vector. function intended used order add columns tibble.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_augment.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Augment Bootstrap P — bootstrap_p_augment","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_augment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Augment Bootstrap P — bootstrap_p_augment","text":"","code":"x <- mtcars$mpg tidy_bootstrap(x) %>% bootstrap_unnest_tbl() %>% bootstrap_p_augment(y) #> # A tibble: 50,000 × 3 #> sim_number y p #> #> 1 1 21.4 0.689 #> 2 1 21.4 0.689 #> 3 1 18.7 0.468 #> 4 1 21.4 0.689 #> 5 1 30.4 0.939 #> 6 1 19.2 0.532 #> 7 1 15.2 0.250 #> 8 1 15.2 0.250 #> 9 1 21.5 0.720 #> 10 1 14.3 0.124 #> # … with 49,990 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute Bootstrap P of a Vector — bootstrap_p_vec","title":"Compute Bootstrap P of a Vector — bootstrap_p_vec","text":"function takes vector input return ecdf probability vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute Bootstrap P of a Vector — bootstrap_p_vec","text":"","code":"bootstrap_p_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute Bootstrap P of a Vector — bootstrap_p_vec","text":".x numeric","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute Bootstrap P of a Vector — bootstrap_p_vec","text":"vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute Bootstrap P of a Vector — bootstrap_p_vec","text":"function return ecdf probability vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compute Bootstrap P of a Vector — bootstrap_p_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_p_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute Bootstrap P of a Vector — bootstrap_p_vec","text":"","code":"x <- mtcars$mpg bootstrap_p_vec(x) #> [1] 0.62500 0.62500 0.78125 0.68750 0.46875 0.43750 0.12500 0.81250 0.78125 #> [10] 0.53125 0.40625 0.34375 0.37500 0.25000 0.06250 0.06250 0.15625 0.96875 #> [19] 0.93750 1.00000 0.71875 0.28125 0.25000 0.09375 0.53125 0.87500 0.84375 #> [28] 0.93750 0.31250 0.56250 0.18750 0.68750"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_augment.html","id":null,"dir":"Reference","previous_headings":"","what":"Augment Bootstrap Q — bootstrap_q_augment","title":"Augment Bootstrap Q — bootstrap_q_augment","text":"Takes numeric vector return quantile.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_augment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Augment Bootstrap Q — bootstrap_q_augment","text":"","code":"bootstrap_q_augment(.data, .value, .names = \"auto\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_augment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Augment Bootstrap Q — bootstrap_q_augment","text":".data data passed augmented function. .value passed rlang::enquo() capture vectors want augment. .names default \"auto\"","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_augment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Augment Bootstrap Q — bootstrap_q_augment","text":"augmented tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_augment.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Augment Bootstrap Q — bootstrap_q_augment","text":"Takes numeric vector return quantile vector. function intended used order add columns tibble.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_augment.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Augment Bootstrap Q — bootstrap_q_augment","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_augment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Augment Bootstrap Q — bootstrap_q_augment","text":"","code":"x <- mtcars$mpg tidy_bootstrap(x) %>% bootstrap_unnest_tbl() %>% bootstrap_q_augment(y) #> # A tibble: 50,000 × 3 #> sim_number y q #> #> 1 1 17.3 10.4 #> 2 1 18.7 10.4 #> 3 1 17.3 10.4 #> 4 1 17.3 10.4 #> 5 1 21.4 10.4 #> 6 1 15 10.4 #> 7 1 14.7 10.4 #> 8 1 15 10.4 #> 9 1 22.8 10.4 #> 10 1 14.3 10.4 #> # … with 49,990 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","title":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","text":"function takes vector input return quantile vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","text":"","code":"bootstrap_q_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","text":".x numeric","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","text":"vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","text":"function return quantile vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_q_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute Bootstrap Q of a Vector — bootstrap_q_vec","text":"","code":"x <- mtcars$mpg bootstrap_q_vec(x) #> [1] 10.4 10.4 13.3 14.3 14.7 15.0 15.2 15.2 15.5 15.8 16.4 17.3 17.8 18.1 18.7 #> [16] 19.2 19.2 19.7 21.0 21.0 21.4 21.4 21.5 22.8 22.8 24.4 26.0 27.3 30.4 30.4 #> [31] 32.4 33.9"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_stat_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Bootstrap Stat Plot — bootstrap_stat_plot","title":"Bootstrap Stat Plot — bootstrap_stat_plot","text":"function produces plot cumulative statistic function applied bootstrap variable tidy_bootstrap() bootstrap_unnest_tbl() applied .","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_stat_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bootstrap Stat Plot — bootstrap_stat_plot","text":"","code":"bootstrap_stat_plot( .data, .value, .stat = \"cmean\", .show_groups = FALSE, .show_ci_labels = TRUE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_stat_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Bootstrap Stat Plot — bootstrap_stat_plot","text":".data data comes either tidy_bootstrap() bootstrap_unnest_tbl() applied . .value value column calculations applied . .stat cumulative statistic function applied .value column. must quoted. default \"cmean\". .show_groups default FALSE, set TRUE get output simulations bootstrap data. .show_ci_labels default TRUE, show last value upper lower quantile. .interactive default FALSE, set TRUE get plotly plot object back.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_stat_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Bootstrap Stat Plot — bootstrap_stat_plot","text":"plot either ggplot2 plotly.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_stat_plot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Bootstrap Stat Plot — bootstrap_stat_plot","text":"function take data either tidy_bootstrap() directly apply bootstrap_unnest_tbl() output. several different cumulative functions can applied data.accepted values : \"cmean\" - Cumulative Mean \"chmean\" - Cumulative Harmonic Mean \"cgmean\" - Cumulative Geometric Mean \"csum\" = Cumulative Sum \"cmedian\" = Cumulative Median \"cmax\" = Cumulative Max \"cmin\" = Cumulative Min \"cprod\" = Cumulative Product \"csd\" = Cumulative Standard Deviation \"cvar\" = Cumulative Variance \"cskewness\" = Cumulative Skewness \"ckurtosis\" = Cumulative Kurtotsis","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_stat_plot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Bootstrap Stat Plot — bootstrap_stat_plot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_stat_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bootstrap Stat Plot — bootstrap_stat_plot","text":"","code":"x <- mtcars$mpg tidy_bootstrap(x) %>% bootstrap_stat_plot(y, \"cmean\") tidy_bootstrap(x, .num_sims = 10) %>% bootstrap_stat_plot(y, .stat = \"chmean\", .show_groups = TRUE, .show_ci_label = FALSE ) #> Warning: Setting '.num_sims' to less than 2000 means that results can be potentially #> unstable. Consider setting to 2000 or more."},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"Unnest data output tidy_bootstrap().","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"","code":"bootstrap_unnest_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":".data data passed tidy_bootstrap() function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"function takes input output tidy_bootstrap() function returns two column tibble. columns sim_number y looks attribute comes using tidy_bootstrap() work unless data comes function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/bootstrap_unnest_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Unnest Tidy Bootstrap Tibble — bootstrap_unnest_tbl","text":"","code":"tb <- tidy_bootstrap(.x = mtcars$mpg) bootstrap_unnest_tbl(tb) #> # A tibble: 50,000 × 2 #> sim_number y #> #> 1 1 15.2 #> 2 1 26 #> 3 1 14.3 #> 4 1 17.8 #> 5 1 15.5 #> 6 1 14.7 #> 7 1 21.4 #> 8 1 15.2 #> 9 1 30.4 #> 10 1 30.4 #> # … with 49,990 more rows bootstrap_unnest_tbl(tb) %>% tidy_distribution_summary_tbl(sim_number) #> # A tibble: 2,000 × 13 #> sim_num…¹ mean_…² media…³ std_val min_val max_val skewn…⁴ kurto…⁵ range iqr #> #> 1 1 20.7 21 5.65 10.4 30.4 0.375 2.32 20 7 #> 2 2 17.1 17.3 3.97 10.4 26 -0.157 2.76 15.6 4 #> 3 3 17.9 18.1 4.26 10.4 30.4 0.979 4.54 20 4.7 #> 4 4 20.2 18.7 6.57 10.4 33.9 0.710 2.46 23.5 9.2 #> 5 5 22.6 21.4 6.97 10.4 33.9 0.247 2.02 23.5 9.5 #> 6 6 17.7 15.8 4.80 10.4 30.4 0.782 3.33 20 6.4 #> 7 7 20.1 18.7 6.18 10.4 32.4 0.621 2.29 22 9.4 #> 8 8 20.5 19.2 6.32 10.4 33.9 0.694 2.66 23.5 8.9 #> 9 9 20.1 19.2 6.15 10.4 32.4 0.749 2.62 22 6.2 #> 10 10 19.3 18.7 5.89 10.4 33.9 0.723 3.59 23.5 5.6 #> # … with 1,990 more rows, 3 more variables: variance , ci_low , #> # ci_high , and abbreviated variable names ¹​sim_number, ²​mean_val, #> # ³​median_val, ⁴​skewness, ⁵​kurtosis"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cgmean.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Geometric Mean — cgmean","title":"Cumulative Geometric Mean — cgmean","text":"function return cumulative geometric mean vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cgmean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Geometric Mean — cgmean","text":"","code":"cgmean(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cgmean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Geometric Mean — cgmean","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cgmean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Geometric Mean — cgmean","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cgmean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Geometric Mean — cgmean","text":"function return cumulative geometric mean vector. exp(cummean(log(.x)))","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/cgmean.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Geometric Mean — cgmean","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cgmean.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Geometric Mean — cgmean","text":"","code":"x <- mtcars$mpg cgmean(x) #> [1] 21.00000 21.00000 21.58363 21.53757 20.93755 20.43547 19.41935 19.98155 #> [9] 20.27666 20.16633 19.93880 19.61678 19.42805 19.09044 18.33287 17.69470 #> [17] 17.50275 18.11190 18.61236 19.17879 19.28342 19.09293 18.90457 18.62961 #> [25] 18.65210 18.92738 19.15126 19.46993 19.33021 19.34242 19.18443 19.25006"},{"path":"https://www.spsanderson.com/TidyDensity/reference/chmean.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Harmonic Mean — chmean","title":"Cumulative Harmonic Mean — chmean","text":"function return cumulative harmonic mean vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/chmean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Harmonic Mean — chmean","text":"","code":"chmean(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/chmean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Harmonic Mean — chmean","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/chmean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Harmonic Mean — chmean","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/chmean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Harmonic Mean — chmean","text":"function return cumulative harmonic mean vector. 1 / (cumsum(1 / .x))","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/chmean.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Harmonic Mean — chmean","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/chmean.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Harmonic Mean — chmean","text":"","code":"x <- mtcars$mpg chmean(x) #> [1] 21.0000000 10.5000000 7.1891892 5.3813575 4.1788087 3.3949947 #> [7] 2.7436247 2.4663044 2.2255626 1.9943841 1.7934398 1.6166494 #> [13] 1.4784877 1.3474251 1.1928760 1.0701322 0.9975150 0.9677213 #> [19] 0.9378663 0.9126181 0.8754572 0.8286539 0.7858140 0.7419753 #> [25] 0.7143688 0.6961523 0.6779989 0.6632076 0.6364908 0.6165699 #> [31] 0.5922267 0.5762786"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":null,"dir":"Reference","previous_headings":"","what":"Confidence Interval Generic — ci_hi","title":"Confidence Interval Generic — ci_hi","text":"Gets upper 97.5% quantile numeric vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Confidence Interval Generic — ci_hi","text":"","code":"ci_hi(.x, .na_rm = FALSE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Confidence Interval Generic — ci_hi","text":".x vector numeric values .na_rm Boolean, defaults FALSE. Passed quantile function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Confidence Interval Generic — ci_hi","text":"numeric value.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Confidence Interval Generic — ci_hi","text":"Gets upper 97.5% quantile numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Confidence Interval Generic — ci_hi","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_hi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Confidence Interval Generic — ci_hi","text":"","code":"x <- mtcars$mpg ci_hi(x) #> [1] 32.7375"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":null,"dir":"Reference","previous_headings":"","what":"Confidence Interval Generic — ci_lo","title":"Confidence Interval Generic — ci_lo","text":"Gets lower 2.5% quantile numeric vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Confidence Interval Generic — ci_lo","text":"","code":"ci_lo(.x, .na_rm = FALSE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Confidence Interval Generic — ci_lo","text":".x vector numeric values .na_rm Boolean, defaults FALSE. Passed quantile function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Confidence Interval Generic — ci_lo","text":"numeric value.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Confidence Interval Generic — ci_lo","text":"Gets lower 2.5% quantile numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Confidence Interval Generic — ci_lo","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ci_lo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Confidence Interval Generic — ci_lo","text":"","code":"x <- mtcars$mpg ci_lo(x) #> [1] 10.4"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ckurtosis.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Kurtosis — ckurtosis","title":"Cumulative Kurtosis — ckurtosis","text":"function return cumulative kurtosis vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ckurtosis.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Kurtosis — ckurtosis","text":"","code":"ckurtosis(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/ckurtosis.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Kurtosis — ckurtosis","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ckurtosis.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Kurtosis — ckurtosis","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ckurtosis.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Kurtosis — ckurtosis","text":"function return cumulative kurtosis vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/ckurtosis.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Kurtosis — ckurtosis","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/ckurtosis.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Kurtosis — ckurtosis","text":"","code":"x <- mtcars$mpg ckurtosis(x) #> [1] NaN NaN 1.500000 2.189216 2.518932 1.786006 2.744467 2.724675 #> [9] 2.930885 2.988093 2.690270 2.269038 2.176622 1.992044 2.839430 2.481896 #> [17] 2.356826 3.877115 3.174702 2.896931 3.000743 3.091225 3.182071 3.212816 #> [25] 3.352916 3.015952 2.837139 2.535185 2.595908 2.691103 2.738468 2.799467"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmean.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Mean — cmean","title":"Cumulative Mean — cmean","text":"function return cumulative mean vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Mean — cmean","text":"","code":"cmean(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Mean — cmean","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Mean — cmean","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Mean — cmean","text":"function return cumulative mean vector. uses dplyr::cummean() basis function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmean.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Mean — cmean","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmean.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Mean — cmean","text":"","code":"x <- mtcars$mpg cmean(x) #> [1] 21.00000 21.00000 21.60000 21.55000 20.98000 20.50000 19.61429 20.21250 #> [9] 20.50000 20.37000 20.13636 19.82500 19.63077 19.31429 18.72000 18.20000 #> [17] 17.99412 18.79444 19.40526 20.13000 20.19524 19.98182 19.77391 19.50417 #> [25] 19.49200 19.79231 20.02222 20.39286 20.23448 20.21667 20.04839 20.09062"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmedian.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Median — cmedian","title":"Cumulative Median — cmedian","text":"function return cumulative median vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmedian.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Median — cmedian","text":"","code":"cmedian(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmedian.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Median — cmedian","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmedian.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Median — cmedian","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmedian.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Median — cmedian","text":"function return cumulative median vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmedian.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Median — cmedian","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cmedian.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Median — cmedian","text":"","code":"x <- mtcars$mpg cmedian(x) #> [1] 21.00 21.00 21.00 21.20 21.00 21.00 21.00 21.00 21.00 21.00 21.00 20.10 #> [13] 19.20 18.95 18.70 18.40 18.10 18.40 18.70 18.95 19.20 18.95 18.70 18.40 #> [25] 18.70 18.95 19.20 19.20 19.20 19.20 19.20 19.20"},{"path":"https://www.spsanderson.com/TidyDensity/reference/color_blind.html","id":null,"dir":"Reference","previous_headings":"","what":"Provide Colorblind Compliant Colors — color_blind","title":"Provide Colorblind Compliant Colors — color_blind","text":"8 Hex RGB color definitions suitable charts colorblind people.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/color_blind.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Provide Colorblind Compliant Colors — color_blind","text":"","code":"color_blind()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/csd.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Standard Deviation — csd","title":"Cumulative Standard Deviation — csd","text":"function return cumulative standard deviation vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/csd.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Standard Deviation — csd","text":"","code":"csd(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/csd.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Standard Deviation — csd","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/csd.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Standard Deviation — csd","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/csd.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Standard Deviation — csd","text":"function return cumulative standard deviation vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/csd.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Standard Deviation — csd","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/csd.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Standard Deviation — csd","text":"","code":"x <- mtcars$mpg csd(x) #> [1] NA 0.0000000 1.0392305 0.8544004 1.4737707 1.7663522 2.8445436 #> [8] 3.1302385 3.0524580 2.9070986 2.8647069 2.9366416 2.8975233 3.0252418 #> [15] 3.7142967 4.1476098 4.1046423 5.2332053 5.7405452 6.4594362 6.3029736 #> [22] 6.2319940 6.1698105 6.1772007 6.0474457 6.1199296 6.1188444 6.3166405 #> [29] 6.2611772 6.1530527 6.1217574 6.0269481"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cskewness.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Skewness — cskewness","title":"Cumulative Skewness — cskewness","text":"function return cumulative skewness vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cskewness.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Skewness — cskewness","text":"","code":"cskewness(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cskewness.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Skewness — cskewness","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cskewness.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Skewness — cskewness","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cskewness.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Skewness — cskewness","text":"function return cumulative skewness vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/cskewness.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Skewness — cskewness","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cskewness.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Skewness — cskewness","text":"","code":"x <- mtcars$mpg cskewness(x) #> [1] NaN NaN 0.707106781 0.997869718 -0.502052297 #> [6] -0.258803244 -0.867969171 -0.628239920 -0.808101715 -0.695348960 #> [11] -0.469220594 -0.256323338 -0.091505282 0.002188142 -0.519593266 #> [16] -0.512660692 -0.379598706 0.614549281 0.581410573 0.649357202 #> [21] 0.631855977 0.706212631 0.775750182 0.821447605 0.844413861 #> [26] 0.716010069 0.614326432 0.525141032 0.582528820 0.601075783 #> [31] 0.652552397 0.640439864"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cvar.html","id":null,"dir":"Reference","previous_headings":"","what":"Cumulative Variance — cvar","title":"Cumulative Variance — cvar","text":"function return cumulative variance vector.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cvar.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cumulative Variance — cvar","text":"","code":"cvar(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/cvar.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cumulative Variance — cvar","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cvar.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cumulative Variance — cvar","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cvar.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Cumulative Variance — cvar","text":"function return cumulative variance vector. exp(cummean(log(.x)))","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/cvar.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Cumulative Variance — cvar","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/cvar.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Cumulative Variance — cvar","text":"","code":"x <- mtcars$mpg cvar(x) #> [1] NA 0.000000 1.080000 0.730000 2.172000 3.120000 8.091429 #> [8] 9.798393 9.317500 8.451222 8.206545 8.623864 8.395641 9.152088 #> [15] 13.796000 17.202667 16.848088 27.386438 32.953860 41.724316 39.727476 #> [22] 38.837749 38.066561 38.157808 36.571600 37.453538 37.440256 39.899947 #> [29] 39.202340 37.860057 37.475914 36.324103"},{"path":"https://www.spsanderson.com/TidyDensity/reference/dist_type_extractor.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","title":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","text":"Get distribution name title case tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/dist_type_extractor.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","text":"","code":"dist_type_extractor(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/dist_type_extractor.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","text":".x attribute list passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/dist_type_extractor.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","text":"character string","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/dist_type_extractor.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","text":"extract distribution type tidy_ distribution function output using attributes object. must pass attribute directly function. meant really used internally. passing using manually $tibble_type attribute.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/dist_type_extractor.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","text":"Steven P. Sanderson II,","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/dist_type_extractor.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract Distribution Type from Tidy Distribution Object — dist_type_extractor","text":"","code":"tn <- tidy_normal() atb <- attributes(tn) dist_type_extractor(atb$tibble_type) #> [1] \"Gaussian\""},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_color_colorblind.html","id":null,"dir":"Reference","previous_headings":"","what":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","title":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","text":"Provide Colorblind Compliant Colors","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_color_colorblind.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","text":"","code":"td_scale_color_colorblind(..., theme = \"td\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_color_colorblind.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Provide Colorblind Compliant Colors — td_scale_color_colorblind","text":"... Data passed function theme defaults td allowed value","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_fill_colorblind.html","id":null,"dir":"Reference","previous_headings":"","what":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","title":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","text":"Provide Colorblind Compliant Colors","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_fill_colorblind.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","text":"","code":"td_scale_fill_colorblind(..., theme = \"td\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/td_scale_fill_colorblind.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Provide Colorblind Compliant Colors — td_scale_fill_colorblind","text":"... Data passed function theme defaults td allowed value","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidyeval.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy eval helpers — tidyeval","title":"Tidy eval helpers — tidyeval","text":"page lists tidy eval tools reexported package rlang. learn using tidy eval scripts packages high level, see dplyr programming vignette ggplot2 packages vignette. Metaprogramming section Advanced R may also useful deeper dive. tidy eval operators {{, !!, !!! syntactic constructs specially interpreted tidy eval functions. mostly need {{, !! !!! advanced operators use simple cases. curly-curly operator {{ allows tunnel data-variables passed function arguments inside tidy eval functions. {{ designed individual arguments. pass multiple arguments contained dots, use ... normal way. enquo() enquos() delay execution one several function arguments. former returns single expression, latter returns list expressions. defused, expressions longer evaluate . must injected back evaluation context !! (single expression) !!! (list expressions). simple case, code equivalent usage {{ ... . Defusing enquo() enquos() needed complex cases, instance need inspect modify expressions way. .data pronoun object represents current slice data. variable name string, use .data pronoun subset variable [[. Another tidy eval operator :=. makes possible use glue curly-curly syntax LHS =. technical reasons, R language support complex expressions left =, use := workaround. Many tidy eval functions like dplyr::mutate() dplyr::summarise() give automatic name unnamed inputs. need create sort automatic names , use as_label(). instance, glue-tunnelling syntax can reproduced manually : Expressions defused enquo() (tunnelled {{) need simple column names, can arbitrarily complex. as_label() handles cases gracefully. code assumes simple column name, use as_name() instead. safer throws error input name expected.","code":"my_function <- function(data, var, ...) { data %>% group_by(...) %>% summarise(mean = mean({{ var }})) } my_function <- function(data, var, ...) { # Defuse var <- enquo(var) dots <- enquos(...) # Inject data %>% group_by(!!!dots) %>% summarise(mean = mean(!!var)) } my_var <- \"disp\" mtcars %>% summarise(mean = mean(.data[[my_var]])) my_function <- function(data, var, suffix = \"foo\") { # Use `{{` to tunnel function arguments and the usual glue # operator `{` to interpolate plain strings. data %>% summarise(\"{{ var }}_mean_{suffix}\" := mean({{ var }})) } my_function <- function(data, var, suffix = \"foo\") { var <- enquo(var) prefix <- as_label(var) data %>% summarise(\"{prefix}_mean_{suffix}\" := mean(!!var)) }"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Density Data — tidy_autoplot","title":"Automatic Plot of Density Data — tidy_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq mcmc number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Density Data — tidy_autoplot","text":"","code":"tidy_autoplot( .data, .plot_type = \"density\", .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Density Data — tidy_autoplot","text":".data data passed tidy_distribution function like tidy_normal() .plot_type quoted string like 'density' .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Density Data — tidy_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Density Data — tidy_autoplot","text":"function spit one following plots: density quantile probability qq mcmc","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Density Data — tidy_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Density Data — tidy_autoplot","text":"","code":"tidy_normal(.num_sims = 5) %>% tidy_autoplot() tidy_normal(.num_sims = 20) %>% tidy_autoplot(.plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bernoulli.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","title":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","text":"function generate n random points Bernoulli distribution user provided, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bernoulli.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","text":"","code":"tidy_bernoulli(.n = 50, .prob = 0.1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bernoulli.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","text":".n number randomly generated points want. .prob probability success/failure. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bernoulli.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bernoulli.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","text":"function uses rbinom(), underlying p, d, q functions. Bernoulli distribution special case Binomial distribution size = 1 hence binom functions used set size = 1.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bernoulli.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bernoulli.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Bernoulli Distribution Tibble — tidy_bernoulli","text":"","code":"tidy_bernoulli() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -0.296 0.0427 0.9 0 #> 2 1 2 0 -0.264 0.108 0.9 0 #> 3 1 3 1 -0.231 0.247 1 1 #> 4 1 4 0 -0.199 0.504 0.9 0 #> 5 1 5 0 -0.166 0.924 0.9 0 #> 6 1 6 0 -0.134 1.52 0.9 0 #> 7 1 7 0 -0.101 2.25 0.9 0 #> 8 1 8 0 -0.0687 2.98 0.9 0 #> 9 1 9 0 -0.0362 3.55 0.9 0 #> 10 1 10 0 -0.00372 3.79 0.9 0 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"function generate n random points beta distribution user provided, .shape1, .shape2, .ncp non-centrality parameter, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"","code":"tidy_beta(.n = 50, .shape1 = 1, .shape2 = 1, .ncp = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":".n number randomly generated points want. .shape1 non-negative parameter Beta distribution. .shape2 non-negative parameter Beta distribution. .ncp non-centrality parameter Beta distribution. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"function uses underlying stats::rbeta(), underlying p, d, q functions. information please see stats::rbeta()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_beta.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Beta Distribution Tibble — tidy_beta","text":"","code":"tidy_beta() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.240 -0.340 0.00181 0 0.254 #> 2 1 2 0.157 -0.307 0.00429 0.0204 0.166 #> 3 1 3 0.565 -0.274 0.00942 0.0408 0.597 #> 4 1 4 0.825 -0.241 0.0192 0.0612 0.872 #> 5 1 5 0.765 -0.208 0.0361 0.0816 0.808 #> 6 1 6 0.869 -0.174 0.0631 0.102 0.918 #> 7 1 7 0.631 -0.141 0.103 0.122 0.667 #> 8 1 8 0.315 -0.108 0.158 0.143 0.333 #> 9 1 9 0.617 -0.0747 0.229 0.163 0.652 #> 10 1 10 0.139 -0.0414 0.314 0.184 0.147 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"function generate n random points binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"","code":"tidy_binomial(.n = 50, .size = 0, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":".n number randomly generated points want. .size Number trials, zero . .prob Probability success trial. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"function uses underlying stats::rbinom(), underlying p, d, q functions. information please see stats::rbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_binomial","text":"","code":"tidy_binomial() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 1 NaN #> 2 1 2 0 -1.18 0.0156 1 NaN #> 3 1 3 0 -1.13 0.0220 1 NaN #> 4 1 4 0 -1.08 0.0305 1 NaN #> 5 1 5 0 -1.03 0.0418 1 NaN #> 6 1 6 0 -0.983 0.0564 1 NaN #> 7 1 7 0 -0.932 0.0749 1 NaN #> 8 1 8 0 -0.882 0.0981 1 NaN #> 9 1 9 0 -0.832 0.126 1 NaN #> 10 1 10 0 -0.781 0.161 1 NaN #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":null,"dir":"Reference","previous_headings":"","what":"Bootstrap Empirical Data — tidy_bootstrap","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"Takes input vector numeric data produces bootstrapped nested tibble simulation number.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"","code":"tidy_bootstrap( .x, .num_sims = 2000, .proportion = 0.8, .distribution_type = \"continuous\" )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Bootstrap Empirical Data — tidy_bootstrap","text":".x vector data passed function. Must numeric vector. .num_sims default 2000, can set anything desired. warning pass console value less 2000. .proportion much original data want pass sampling function. default 0.80 (80%) .distribution_type can either 'continuous' 'discrete'","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"nested tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"function take numeric input vector produce tibble bootstrapped values list. table output two columns: sim_number bootstrap_samples sim_number corresponds many times want data resampled, bootstrap_samples column contains list boostrapped resampled data.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_bootstrap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bootstrap Empirical Data — tidy_bootstrap","text":"","code":"x <- mtcars$mpg tidy_bootstrap(x) #> # A tibble: 2,000 × 2 #> sim_number bootstrap_samples #> #> 1 1 #> 2 2 #> 3 3 #> 4 4 #> 5 5 #> 6 6 #> 7 7 #> 8 8 #> 9 9 #> 10 10 #> # … with 1,990 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"function generate n random points Burr distribution user provided, .shape1, .shape2, .scale, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"","code":"tidy_burr( .n = 50, .shape1 = 1, .shape2 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":".n number randomly generated points want. .shape1 Must strictly positive. .shape2 Must strictly positive. .rate alternative way specify .scale. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"function uses underlying actuar::rburr(), underlying p, d, q functions. information please see actuar::rburr()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_burr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Burr Distribution Tibble — tidy_burr","text":"","code":"tidy_burr() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 2.13 -4.89 0.00107 0 0.00569 #> 2 1 2 0.325 2.98 0.0840 0.0200 0.000845 #> 3 1 3 0.756 10.8 0.00853 0.0392 0.00199 #> 4 1 4 0.225 18.7 0.00426 0.0577 0.000579 #> 5 1 5 0.278 26.6 0.00380 0.0755 0.000719 #> 6 1 6 33.9 34.5 0.0133 0.0926 0.0990 #> 7 1 7 3.10 42.3 0.00446 0.109 0.00830 #> 8 1 8 41.7 50.2 0.0000000125 0.125 0.125 #> 9 1 9 0.447 58.1 0 0.140 0.00117 #> 10 1 10 1.81 65.9 0 0.155 0.00481 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"function generate n random points cauchy distribution user provided, .location, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"","code":"tidy_cauchy(.n = 50, .location = 0, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":".n number randomly generated points want. .location location parameter. .scale scale parameter, must greater equal 0. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"function uses underlying stats::rcauchy(), underlying p, d, q functions. information please see stats::rcauchy()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_cauchy.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy","text":"","code":"tidy_cauchy() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.957 -23.7 2.14e- 4 0.5 0.656 #> 2 1 2 0.141 -22.9 7.60e- 3 0.506 0.553 #> 3 1 3 1.30 -22.2 1.67e- 2 0.513 0.702 #> 4 1 4 -0.385 -21.4 2.22e- 3 0.519 0.491 #> 5 1 5 1.17 -20.7 1.84e- 5 0.526 0.685 #> 6 1 6 1.56 -19.9 8.65e- 9 0.532 0.738 #> 7 1 7 0.529 -19.2 2.87e-13 0.539 0.601 #> 8 1 8 11.7 -18.4 1.26e-17 0.545 Inf #> 9 1 9 -0.0820 -17.7 5.45e-19 0.552 0.526 #> 10 1 10 -1.25 -16.9 0 0.558 0.396 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"function generate n random points chisquare distribution user provided, .df, .ncp, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"","code":"tidy_chisquare(.n = 50, .df = 1, .ncp = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":".n number randomly generated points want. .df Degrees freedom (non-negative can non-integer) .ncp Non-centrality parameter, must non-negative. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"function uses underlying stats::rchisq(), underlying p, d, q functions. information please see stats::rchisq()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_chisquare.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble — tidy_chisquare","text":"","code":"tidy_chisquare() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 4.56 -3.13 0.00110 0 0.631 #> 2 1 2 0.905 -2.76 0.00313 0.0691 0.0245 #> 3 1 3 1.40 -2.39 0.00787 0.0978 0.0589 #> 4 1 4 0.813 -2.02 0.0176 0.120 0.0198 #> 5 1 5 1.70 -1.65 0.0348 0.138 0.0869 #> 6 1 6 6.49 -1.27 0.0615 0.155 1.32 #> 7 1 7 2.28 -0.902 0.0969 0.169 0.156 #> 8 1 8 0.129 -0.531 0.136 0.183 0.000495 #> 9 1 9 0.603 -0.159 0.173 0.195 0.0109 #> 10 1 10 6.31 0.212 0.197 0.207 1.24 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"","code":"tidy_combined_autoplot( .data, .plot_type = \"density\", .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":".data data passed function tidy_multi_dist() .plot_type quoted string like 'density' .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"function spit one following plots: density quantile probability qq","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combined_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Combined Multi Dist Data — tidy_combined_autoplot","text":"","code":"combined_tbl <- tidy_combine_distributions( tidy_normal(), tidy_gamma(), tidy_beta() ) combined_tbl #> # A tibble: 150 × 8 #> sim_number x y dx dy p q dist_type #> #> 1 1 1 0.275 -4.15 0.000206 0.608 0.275 Gaussian c(0, 1) #> 2 1 2 1.27 -3.99 0.000583 0.898 1.27 Gaussian c(0, 1) #> 3 1 3 -0.267 -3.83 0.00144 0.395 -0.267 Gaussian c(0, 1) #> 4 1 4 -1.43 -3.67 0.00312 0.0765 -1.43 Gaussian c(0, 1) #> 5 1 5 -0.464 -3.51 0.00594 0.321 -0.464 Gaussian c(0, 1) #> 6 1 6 -1.91 -3.34 0.00997 0.0283 -1.91 Gaussian c(0, 1) #> 7 1 7 -0.644 -3.18 0.0150 0.260 -0.644 Gaussian c(0, 1) #> 8 1 8 -1.52 -3.02 0.0204 0.0638 -1.52 Gaussian c(0, 1) #> 9 1 9 1.14 -2.86 0.0263 0.874 1.14 Gaussian c(0, 1) #> 10 1 10 -0.441 -2.70 0.0335 0.329 -0.441 Gaussian c(0, 1) #> # … with 140 more rows combined_tbl %>% tidy_combined_autoplot() combined_tbl %>% tidy_combined_autoplot(.plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":null,"dir":"Reference","previous_headings":"","what":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"allows user specify n number tidy_ distributions can combined single tibble. preferred method combining multiple distributions different types, example Gaussian distribution Beta distribution. generates single tibble added column dist_type give distribution family name associated parameters.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"","code":"tidy_combine_distributions(...)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"... ... can place different distributions","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"Allows user generate tibble different tidy_ distributions","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_combine_distributions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Combine Multiple Tidy Distributions of Different Types — tidy_combine_distributions","text":"","code":"tn <- tidy_normal() tb <- tidy_beta() tc <- tidy_cauchy() tidy_combine_distributions(tn, tb, tc) #> # A tibble: 150 × 8 #> sim_number x y dx dy p q dist_type #> #> 1 1 1 -0.459 -3.12 0.000257 0.323 -0.459 Gaussian c(0, 1) #> 2 1 2 -0.224 -2.99 0.000695 0.411 -0.224 Gaussian c(0, 1) #> 3 1 3 0.380 -2.87 0.00168 0.648 0.380 Gaussian c(0, 1) #> 4 1 4 1.95 -2.74 0.00365 0.975 1.95 Gaussian c(0, 1) #> 5 1 5 -1.48 -2.61 0.00714 0.0699 -1.48 Gaussian c(0, 1) #> 6 1 6 -0.532 -2.49 0.0127 0.297 -0.532 Gaussian c(0, 1) #> 7 1 7 1.83 -2.36 0.0208 0.966 1.83 Gaussian c(0, 1) #> 8 1 8 1.19 -2.24 0.0315 0.884 1.19 Gaussian c(0, 1) #> 9 1 9 0.230 -2.11 0.0449 0.591 0.230 Gaussian c(0, 1) #> 10 1 10 0.620 -1.99 0.0604 0.732 0.620 Gaussian c(0, 1) #> # … with 140 more rows ## OR tidy_combine_distributions( tidy_normal(), tidy_beta(), tidy_cauchy(), tidy_logistic() ) #> # A tibble: 200 × 8 #> sim_number x y dx dy p q dist_type #> #> 1 1 1 1.34 -4.01 0.000181 0.910 1.34 Gaussian c(0, 1) #> 2 1 2 0.625 -3.83 0.000508 0.734 0.625 Gaussian c(0, 1) #> 3 1 3 1.69 -3.64 0.00126 0.954 1.69 Gaussian c(0, 1) #> 4 1 4 -0.331 -3.46 0.00281 0.370 -0.331 Gaussian c(0, 1) #> 5 1 5 1.14 -3.27 0.00559 0.874 1.14 Gaussian c(0, 1) #> 6 1 6 -0.391 -3.08 0.0101 0.348 -0.391 Gaussian c(0, 1) #> 7 1 7 1.95 -2.90 0.0167 0.974 1.95 Gaussian c(0, 1) #> 8 1 8 -1.90 -2.71 0.0256 0.0286 -1.90 Gaussian c(0, 1) #> 9 1 9 -1.85 -2.52 0.0372 0.0320 -1.85 Gaussian c(0, 1) #> 10 1 10 -1.19 -2.34 0.0516 0.116 -1.19 Gaussian c(0, 1) #> # … with 190 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":null,"dir":"Reference","previous_headings":"","what":"Compare Empirical Data to Distributions — tidy_distribution_comparison","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"Compare empirical data set different distributions help find distribution best fit.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"","code":"tidy_distribution_comparison(.x, .distribution_type = \"continuous\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":".x data set passed function .distribution_type kind data , can one continuous discrete","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"invisible list object. tibble printed.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"purpose function take data set provided try find distribution may fit best. parameter .distribution_type must set either continuous discrete order function try appropriate types distributions. following distributions used: Continuous: tidy_beta tidy_cauchy tidy_exponential tidy_gamma tidy_logistic tidy_lognormal tidy_normal tidy_pareto tidy_uniform tidy_weibull Discrete: tidy_binomial tidy_geometric tidy_hypergeometric tidy_poisson function returns list output tibbles. tibbles returned: comparison_tbl deviance_tbl total_deviance_tbl aic_tbl kolmogorov_smirnov_tbl multi_metric_tbl comparison_tbl long tibble lists values density function given data. deviance_tbl total_deviance_tbl just give simple difference actual density estimated density given estimated distribution. aic_tbl provide AIC lm model estimated density emprical density. kolmogorov_smirnov_tbl now provides two.sided estimate ks.test estimated density empirical. multi_metric_tbl summarise metrics single tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_comparison.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compare Empirical Data to Distributions — tidy_distribution_comparison","text":"","code":"xc <- mtcars$mpg output_c <- tidy_distribution_comparison(xc, \"continuous\") #> For the beta distribution, its mean 'mu' should be 0 < mu < 1. The data will #> therefore be scaled to enforce this. xd <- trunc(xc) output_d <- tidy_distribution_comparison(xd, \"discrete\") output_c #> $comparison_tbl #> # A tibble: 352 × 8 #> sim_number x y dx dy p q dist_type #> #> 1 1 1 21 2.97 0.000114 0.625 10.4 Empirical #> 2 1 2 21 4.21 0.000455 0.625 10.4 Empirical #> 3 1 3 22.8 5.44 0.00142 0.781 13.3 Empirical #> 4 1 4 21.4 6.68 0.00355 0.688 14.3 Empirical #> 5 1 5 18.7 7.92 0.00721 0.469 14.7 Empirical #> 6 1 6 18.1 9.16 0.0124 0.438 15 Empirical #> 7 1 7 14.3 10.4 0.0192 0.125 15.2 Empirical #> 8 1 8 24.4 11.6 0.0281 0.812 15.2 Empirical #> 9 1 9 22.8 12.9 0.0395 0.781 15.5 Empirical #> 10 1 10 19.2 14.1 0.0516 0.531 15.8 Empirical #> # … with 342 more rows #> #> $deviance_tbl #> # A tibble: 352 × 2 #> name value #> #> 1 Empirical 0.451 #> 2 Beta c(1.11, 1.58, 0) 0.145 #> 3 Cauchy c(19.2, 7.38) -0.549 #> 4 Exponential c(0.05) 0.301 #> 5 Gamma c(11.47, 1.75) 0.451 #> 6 Logistic c(20.09, 3.27) -0.0963 #> 7 Lognormal c(2.96, 0.29) -0.0212 #> 8 Pareto c(10.4, 1.62) 0.427 #> 9 Uniform c(8.34, 31.84) -0.160 #> 10 Weibull c(3.58, 22.29) -0.259 #> # … with 342 more rows #> #> $total_deviance_tbl #> # A tibble: 10 × 2 #> dist_with_params abs_tot_deviance #> #> 1 Cauchy c(19.2, 7.38) 0.181 #> 2 Beta c(1.11, 1.58, 0) 1.11 #> 3 Uniform c(8.34, 31.84) 2.58 #> 4 Weibull c(3.58, 22.29) 3.68 #> 5 Gamma c(11.47, 1.75) 3.88 #> 6 Lognormal c(2.96, 0.29) 4.81 #> 7 Gaussian c(20.09, 5.93) 6.03 #> 8 Pareto c(10.4, 1.62) 6.69 #> 9 Exponential c(0.05) 7.20 #> 10 Logistic c(20.09, 3.27) 8.75 #> #> $aic_tbl #> # A tibble: 10 × 3 #> dist_type aic_value abs_aic #> #> 1 Beta c(1.11, 1.58, 0) -3.22 3.22 #> 2 Pareto c(10.4, 1.62) 79.9 79.9 #> 3 Logistic c(20.09, 3.27) -139. 139. #> 4 Gaussian c(20.09, 5.93) -144. 144. #> 5 Lognormal c(2.96, 0.29) -157. 157. #> 6 Gamma c(11.47, 1.75) -176. 176. #> 7 Weibull c(3.58, 22.29) -177. 177. #> 8 Uniform c(8.34, 31.84) -180. 180. #> 9 Exponential c(0.05) -196. 196. #> 10 Cauchy c(19.2, 7.38) -279. 279. #> #> $kolmogorov_smirnov_tbl #> # A tibble: 10 × 6 #> dist_type ks_statistic ks_pvalue ks_method alter…¹ dist_…² #> #> 1 Beta c(1.11, 1.58, 0) 0.781 0.000500 Monte-Carlo t… two-si… Beta c… #> 2 Cauchy c(19.2, 7.38) 0.531 0.000500 Monte-Carlo t… two-si… Cauchy… #> 3 Exponential c(0.05) 0.438 0.00400 Monte-Carlo t… two-si… Expone… #> 4 Gamma c(11.47, 1.75) 0.188 0.651 Monte-Carlo t… two-si… Gamma … #> 5 Logistic c(20.09, 3.27) 0.219 0.417 Monte-Carlo t… two-si… Logist… #> 6 Lognormal c(2.96, 0.29) 0.156 0.843 Monte-Carlo t… two-si… Lognor… #> 7 Pareto c(10.4, 1.62) 0.844 0.000500 Monte-Carlo t… two-si… Pareto… #> 8 Uniform c(8.34, 31.84) 0.156 0.841 Monte-Carlo t… two-si… Unifor… #> 9 Weibull c(3.58, 22.29) 0.188 0.642 Monte-Carlo t… two-si… Weibul… #> 10 Gaussian c(20.09, 5.93) 0.219 0.434 Monte-Carlo t… two-si… Gaussi… #> # … with abbreviated variable names ¹​alternative, ²​dist_char #> #> $multi_metric_tbl #> # A tibble: 10 × 8 #> dist_type abs_t…¹ aic_v…² abs_aic ks_st…³ ks_pv…⁴ ks_me…⁵ alter…⁶ #> #> 1 Cauchy c(19.2, 7.38) 0.181 -279. 279. 0.531 5.00e-4 Monte-… two-si… #> 2 Beta c(1.11, 1.58, 0) 1.11 -3.22 3.22 0.781 5.00e-4 Monte-… two-si… #> 3 Uniform c(8.34, 31.8… 2.58 -180. 180. 0.156 8.41e-1 Monte-… two-si… #> 4 Weibull c(3.58, 22.2… 3.68 -177. 177. 0.188 6.42e-1 Monte-… two-si… #> 5 Gamma c(11.47, 1.75) 3.88 -176. 176. 0.188 6.51e-1 Monte-… two-si… #> 6 Lognormal c(2.96, 0.… 4.81 -157. 157. 0.156 8.43e-1 Monte-… two-si… #> 7 Gaussian c(20.09, 5.… 6.03 -144. 144. 0.219 4.34e-1 Monte-… two-si… #> 8 Pareto c(10.4, 1.62) 6.69 79.9 79.9 0.844 5.00e-4 Monte-… two-si… #> 9 Exponential c(0.05) 7.20 -196. 196. 0.438 4.00e-3 Monte-… two-si… #> 10 Logistic c(20.09, 3.… 8.75 -139. 139. 0.219 4.17e-1 Monte-… two-si… #> # … with abbreviated variable names ¹​abs_tot_deviance, ²​aic_value, #> # ³​ks_statistic, ⁴​ks_pvalue, ⁵​ks_method, ⁶​alternative #> #> attr(,\".x\") #> [1] 21.0 21.0 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 17.8 16.4 17.3 15.2 10.4 #> [16] 10.4 14.7 32.4 30.4 33.9 21.5 15.5 15.2 13.3 19.2 27.3 26.0 30.4 15.8 19.7 #> [31] 15.0 21.4 #> attr(,\".n\") #> [1] 32"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"function returns summary statistics tibble. use y column tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"","code":"tidy_distribution_summary_tbl(.data, ...)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":".data data going passed tidy_ distribution function. ... grouping variable gets passed dplyr::group_by() dplyr::select().","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"summary stats tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"function takes tidy_ distribution table return tibble following information: sim_number mean_val median_val std_val min_val max_val skewness kurtosis range iqr variance ci_hi ci_lo kurtosis skewness come package healthyR.ai","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_distribution_summary_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Distribution Summary Statistics Tibble — tidy_distribution_summary_tbl","text":"","code":"library(dplyr) #> #> Attaching package: 'dplyr' #> The following objects are masked from 'package:stats': #> #> filter, lag #> The following objects are masked from 'package:base': #> #> intersect, setdiff, setequal, union tn <- tidy_normal(.num_sims = 5) tb <- tidy_beta(.num_sims = 5) tidy_distribution_summary_tbl(tn) #> # A tibble: 1 × 12 #> mean_val median_…¹ std_val min_val max_val skewn…² kurto…³ range iqr varia…⁴ #> #> 1 -0.0127 0.0901 0.989 -2.51 2.61 -0.0150 2.75 5.13 1.28 0.978 #> # … with 2 more variables: ci_low , ci_high , and abbreviated #> # variable names ¹​median_val, ²​skewness, ³​kurtosis, ⁴​variance tidy_distribution_summary_tbl(tn, sim_number) #> # A tibble: 5 × 13 #> sim_num…¹ mean_…² median…³ std_val min_val max_val skewn…⁴ kurto…⁵ range iqr #> #> 1 1 -0.0366 -0.0916 1.03 -2.09 2.24 -0.0411 2.38 4.34 1.39 #> 2 2 -0.0144 0.00540 0.976 -2.42 2.21 -0.194 3.00 4.64 1.06 #> 3 3 0.196 0.199 1.06 -2.13 2.61 0.0230 2.63 4.75 1.42 #> 4 4 -0.109 -0.0785 0.951 -1.96 1.89 0.0450 2.16 3.85 1.48 #> 5 5 -0.0998 0.0508 0.923 -2.51 2.28 -0.0897 3.56 4.79 0.998 #> # … with 3 more variables: variance , ci_low , ci_high , and #> # abbreviated variable names ¹​sim_number, ²​mean_val, ³​median_val, ⁴​skewness, #> # ⁵​kurtosis data_tbl <- tidy_combine_distributions(tn, tb) tidy_distribution_summary_tbl(data_tbl) #> # A tibble: 1 × 12 #> mean_val median_…¹ std_val min_val max_val skewn…² kurto…³ range iqr varia…⁴ #> #> 1 0.230 0.330 0.767 -2.51 2.61 -0.732 4.38 5.13 0.658 0.589 #> # … with 2 more variables: ci_low , ci_high , and abbreviated #> # variable names ¹​median_val, ²​skewness, ³​kurtosis, ⁴​variance tidy_distribution_summary_tbl(data_tbl, dist_type) #> # A tibble: 2 × 13 #> dist_type mean_…¹ media…² std_val min_val max_val skewn…³ kurto…⁴ range iqr #> #> 1 Gaussian… -0.0127 0.0901 0.989 -2.51 2.61 -0.0150 2.75 5.13 1.28 #> 2 Beta c(1… 0.472 0.452 0.289 0.00252 0.999 0.145 1.87 0.996 0.486 #> # … with 3 more variables: variance , ci_low , ci_high , and #> # abbreviated variable names ¹​mean_val, ²​median_val, ³​skewness, ⁴​kurtosis"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Empirical — tidy_empirical","title":"Tidy Empirical — tidy_empirical","text":"function takes single argument .x vector return tibble information similar tidy_ distribution functions. y column set equal dy density function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Empirical — tidy_empirical","text":"","code":"tidy_empirical(.x, .num_sims = 1, .distribution_type = \"continuous\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Empirical — tidy_empirical","text":".x vector numbers .num_sims many simulations run, defaults 1. .distribution_type string either \"continuous\" \"discrete\". function default \"continuous\"","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Empirical — tidy_empirical","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Empirical — tidy_empirical","text":"function takes single argument .x vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Empirical — tidy_empirical","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_empirical.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Empirical — tidy_empirical","text":"","code":"x <- mtcars$mpg tidy_empirical(.x = x, .distribution_type = \"continuous\") #> # A tibble: 32 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 21 2.97 0.000114 0.625 10.4 #> 2 1 2 21 4.21 0.000455 0.625 10.4 #> 3 1 3 22.8 5.44 0.00142 0.781 13.3 #> 4 1 4 21.4 6.68 0.00355 0.688 14.3 #> 5 1 5 18.7 7.92 0.00721 0.469 14.7 #> 6 1 6 18.1 9.16 0.0124 0.438 15 #> 7 1 7 14.3 10.4 0.0192 0.125 15.2 #> 8 1 8 24.4 11.6 0.0281 0.812 15.2 #> 9 1 9 22.8 12.9 0.0395 0.781 15.5 #> 10 1 10 19.2 14.1 0.0516 0.531 15.8 #> # … with 22 more rows tidy_empirical(.x = x, .num_sims = 10, .distribution_type = \"continuous\") #> # A tibble: 320 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 15 6.83 0.000309 0.188 13.3 #> 2 1 2 17.8 7.91 0.00130 0.406 13.3 #> 3 1 3 13.3 8.99 0.00436 0.0938 13.3 #> 4 1 4 14.3 10.1 0.0117 0.125 13.3 #> 5 1 5 13.3 11.2 0.0251 0.0938 14.3 #> 6 1 6 19.2 12.2 0.0437 0.531 14.7 #> 7 1 7 21.4 13.3 0.0623 0.688 14.7 #> 8 1 8 21 14.4 0.0740 0.625 15 #> 9 1 9 21.5 15.5 0.0759 0.719 15 #> 10 1 10 15.2 16.6 0.0716 0.25 15 #> # … with 310 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"function generate n random points exponential distribution user provided, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"","code":"tidy_exponential(.n = 50, .rate = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":".n number randomly generated points want. .rate vector rates .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"function uses underlying stats::rexp(), underlying p, d, q functions. information please see stats::rexp()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_exponential.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential","text":"","code":"tidy_exponential() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.761 -0.900 0.00101 0 0.173 #> 2 1 2 3.93 -0.766 0.00399 0.0202 1.76 #> 3 1 3 0.153 -0.633 0.0132 0.0400 0.0308 #> 4 1 4 0.00963 -0.499 0.0367 0.0594 0 #> 5 1 5 0.220 -0.365 0.0863 0.0784 0.0455 #> 6 1 6 2.40 -0.231 0.172 0.0970 0.704 #> 7 1 7 0.970 -0.0976 0.294 0.115 0.227 #> 8 1 8 0.475 0.0362 0.432 0.133 0.104 #> 9 1 9 3.34 0.170 0.552 0.151 1.21 #> 10 1 10 0.698 0.304 0.623 0.168 0.157 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated F Distribution Tibble — tidy_f","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"function generate n random points rf distribution user provided, df1,df2, ncp, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"","code":"tidy_f(.n = 50, .df1 = 1, .df2 = 1, .ncp = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":".n number randomly generated points want. .df1 Degrees freedom, Inf allowed. .df2 Degrees freedom, Inf allowed. .ncp Non-centrality parameter. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"function uses underlying stats::rf(), underlying p, d, q functions. information please see stats::rf()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_f.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated F Distribution Tibble — tidy_f","text":"","code":"tidy_f() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.0596 -4.14 1.15e- 1 0 7.51e-11 #> 2 1 2 111. 210. 8.13e-19 0.0903 2.79e- 4 #> 3 1 3 0.378 423. 0 0.127 3.18e- 9 #> 4 1 4 1072. 637. 0 0.154 2.63e- 2 #> 5 1 5 350. 851. 0 0.177 2.76e- 3 #> 6 1 6 279. 1065. 2.53e- 3 0.197 1.75e- 3 #> 7 1 7 5.11 1278. 4.42e-19 0.214 5.87e- 7 #> 8 1 8 41.9 1492. 0 0.230 3.95e- 5 #> 9 1 9 0.954 1706. 0 0.244 2.04e- 8 #> 10 1 10 10466. 1920. 1.04e-18 0.258 Inf #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Density Data — tidy_four_autoplot","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"","code":"tidy_four_autoplot( .data, .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":".data data passed tidy_distribution function like tidy_normal() .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"function spit one following plots: density quantile probability qq","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_four_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Density Data — tidy_four_autoplot","text":"","code":"tidy_normal(.num_sims = 5) %>% tidy_four_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"function generate n random points gamma distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"","code":"tidy_gamma(.n = 50, .shape = 1, .scale = 0.3, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":".n number randomly generated points want. .shape strictly 0 infinity. .scale standard deviation randomly generated data. strictly 0 infinity. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"function uses underlying stats::rgamma(), underlying p, d, q functions. information please see stats::rgamma()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_gamma.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Gamma Distribution Tibble — tidy_gamma","text":"","code":"tidy_gamma() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.200 -0.392 0.00348 0 0.0483 #> 2 1 2 0.370 -0.348 0.00959 0.0658 0.0968 #> 3 1 3 0.644 -0.305 0.0239 0.127 0.197 #> 4 1 4 1.34 -0.262 0.0541 0.185 Inf #> 5 1 5 0.00311 -0.218 0.111 0.238 0.000338 #> 6 1 6 0.739 -0.175 0.209 0.288 0.241 #> 7 1 7 0.238 -0.132 0.357 0.335 0.0585 #> 8 1 8 0.150 -0.0884 0.559 0.379 0.0353 #> 9 1 9 0.212 -0.0451 0.806 0.420 0.0515 #> 10 1 10 0.633 -0.00179 1.07 0.458 0.192 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"function generate n random points generalized beta distribution user provided, .shape1, .shape2, .shape3, .rate, /.sclae, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"","code":"tidy_generalized_beta( .n = 50, .shape1 = 1, .shape2 = 1, .shape3 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":".n number randomly generated points want. .shape1 non-negative parameter Beta distribution. .shape2 non-negative parameter Beta distribution. .shape3 non-negative parameter Beta distribution. .rate alternative way specify .scale parameter. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"function uses underlying stats::rbeta(), underlying p, d, q functions. information please see stats::rbeta()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_beta.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Generalized Beta Distribution Tibble — tidy_generalized_beta","text":"","code":"tidy_generalized_beta() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.0663 -0.324 0.00470 0 0.0527 #> 2 1 2 0.484 -0.292 0.0110 0.0204 0.506 #> 3 1 3 0.556 -0.259 0.0238 0.0408 0.584 #> 4 1 4 0.838 -0.226 0.0477 0.0612 0.891 #> 5 1 5 0.0724 -0.193 0.0883 0.0816 0.0593 #> 6 1 6 0.0187 -0.161 0.151 0.102 0.000917 #> 7 1 7 0.750 -0.128 0.240 0.122 0.795 #> 8 1 8 0.0918 -0.0951 0.354 0.143 0.0804 #> 9 1 9 0.341 -0.0624 0.487 0.163 0.351 #> 10 1 10 0.693 -0.0296 0.625 0.184 0.733 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"function generate n random points generalized Pareto distribution user provided, .shape1, .shape2, .rate .scale number #' random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"","code":"tidy_generalized_pareto( .n = 50, .shape1 = 1, .shape2 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":".n number randomly generated points want. .shape1 Must positive. .shape2 Must positive. .rate alternative way specify .scale argument .scale Must positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"function uses underlying actuar::rgenpareto(), underlying p, d, q functions. information please see actuar::rgenpareto()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_generalized_pareto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Generalized Pareto Distribution Tibble — tidy_generalized_pareto","text":"","code":"tidy_generalized_pareto() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.63 -1.53 0.000828 0 0.0564 #> 2 1 2 3.78 -0.846 0.0277 0.02 0.142 #> 3 1 3 4.32 -0.163 0.206 0.0392 0.166 #> 4 1 4 0.807 0.520 0.404 0.0577 0.0272 #> 5 1 5 0.527 1.20 0.287 0.0755 0.0176 #> 6 1 6 3.28 1.89 0.155 0.0926 0.121 #> 7 1 7 2.27 2.57 0.0793 0.109 0.0808 #> 8 1 8 0.586 3.25 0.0606 0.125 0.0196 #> 9 1 9 8.19 3.93 0.0527 0.140 0.368 #> 10 1 10 1.52 4.62 0.0348 0.155 0.0526 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"function generate n random points geometric distribution user provided, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"","code":"tidy_geometric(.n = 50, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":".n number randomly generated points want. .prob probability success trial 0 < prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"function uses underlying stats::rgeom(), underlying p, d, q functions. information please see stats::rgeom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_geometric.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric","text":"","code":"tidy_geometric() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 1 NaN #> 2 1 2 0 -1.18 0.0156 1 NaN #> 3 1 3 0 -1.13 0.0220 1 NaN #> 4 1 4 0 -1.08 0.0305 1 NaN #> 5 1 5 0 -1.03 0.0418 1 NaN #> 6 1 6 0 -0.983 0.0564 1 NaN #> 7 1 7 0 -0.932 0.0749 1 NaN #> 8 1 8 0 -0.882 0.0981 1 NaN #> 9 1 9 0 -0.832 0.126 1 NaN #> 10 1 10 0 -0.781 0.161 1 NaN #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"function generate n random points hypergeometric distribution user provided, m,nn, k, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"","code":"tidy_hypergeometric(.n = 50, .m = 0, .nn = 0, .k = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":".n number randomly generated points want. .m number white balls urn .nn number black balls urn .k number balls drawn fro urn. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"function uses underlying stats::rhyper(), underlying p, d, q functions. information please see stats::rhyper()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_hypergeometric.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Hypergeometric Distribution Tibble — tidy_hypergeometric","text":"","code":"tidy_hypergeometric() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 1 NaN #> 2 1 2 0 -1.18 0.0156 1 NaN #> 3 1 3 0 -1.13 0.0220 1 NaN #> 4 1 4 0 -1.08 0.0305 1 NaN #> 5 1 5 0 -1.03 0.0418 1 NaN #> 6 1 6 0 -0.983 0.0564 1 NaN #> 7 1 7 0 -0.932 0.0749 1 NaN #> 8 1 8 0 -0.882 0.0981 1 NaN #> 9 1 9 0 -0.832 0.126 1 NaN #> 10 1 10 0 -0.781 0.161 1 NaN #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"function generate n random points Inverse Burr distribution user provided, .shape1, .shape2, .scale, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"","code":"tidy_inverse_burr( .n = 50, .shape1 = 1, .shape2 = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":".n number randomly generated points want. .shape1 Must strictly positive. .shape2 Must strictly positive. .rate alternative way specify .scale. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"function uses underlying actuar::rinvburr(), underlying p, d, q functions. information please see actuar::rinvburr()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_burr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Burr Distribution Tibble — tidy_inverse_burr","text":"","code":"tidy_inverse_burr() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 66.8 -1.32 0.00158 0 Inf #> 2 1 2 0.319 0.100 0.354 0.02 0.00412 #> 3 1 3 1.11 1.52 0.209 0.0392 0.0162 #> 4 1 4 1.41 2.94 0.0307 0.0577 0.0208 #> 5 1 5 11.1 4.36 0.000404 0.0755 0.198 #> 6 1 6 0.209 5.78 0.0205 0.0926 0.00246 #> 7 1 7 1.15 7.19 0.0238 0.109 0.0168 #> 8 1 8 1.09 8.61 0.000346 0.125 0.0158 #> 9 1 9 2.58 10.0 0.00191 0.140 0.0394 #> 10 1 10 23.8 11.5 0.0286 0.155 0.551 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"function generate n random points inverse exponential distribution user provided, .rate .scale number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"","code":"tidy_inverse_exponential(.n = 50, .rate = 1, .scale = 1/.rate, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":".n number randomly generated points want. .rate alternative way specify .scale .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"function uses underlying actuar::rinvexp(), underlying p, d, q functions. information please see actuar::rinvexp()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_exponential.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Exponential Distribution Tibble — tidy_inverse_exponential","text":"","code":"tidy_inverse_exponential() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.570 -1.54 4.57e- 2 0 0.125 #> 2 1 2 6.58 16.8 1.03e-17 5.24e-22 0.202 #> 3 1 3 2.38 35.2 0 2.29e-11 0.165 #> 4 1 4 1.74 53.6 2.26e-19 8.06e- 8 0.156 #> 5 1 5 0.890 71.9 4.94e- 4 4.79e- 6 0.138 #> 6 1 6 0.408 90.3 4.56e-19 5.55e- 5 0.114 #> 7 1 7 1.82 109. 0 2.84e- 4 0.157 #> 8 1 8 0.957 127. 0 9.12e- 4 0.139 #> 9 1 9 0.272 145. 2.21e-18 2.19e- 3 0.0819 #> 10 1 10 1.33 164. 0 4.32e- 3 0.148 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"function generate n random points inverse gamma distribution user provided, .shape, .rate, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"","code":"tidy_inverse_gamma( .n = 50, .shape = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":".n number randomly generated points want. .shape Must strictly positive. .rate alternative way specify .scale .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"function uses underlying actuar::rinvgamma(), underlying p, d, q functions. information please see actuar::rinvgamma()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_gamma.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Gamma Distribution Tibble — tidy_inverse_gamma","text":"","code":"tidy_inverse_gamma() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.788 -0.741 0.00193 0 0.220 #> 2 1 2 0.573 0.167 0.327 5.24e-22 0.193 #> 3 1 3 0.341 1.07 0.449 2.29e-11 0.107 #> 4 1 4 0.526 1.98 0.0920 8.06e- 8 0.185 #> 5 1 5 0.978 2.89 0.0315 4.79e- 6 0.239 #> 6 1 6 0.399 3.80 0.0305 5.55e- 5 0.153 #> 7 1 7 8.08 4.70 0.0229 2.84e- 4 0.589 #> 8 1 8 0.809 5.61 0.0227 9.12e- 4 0.222 #> 9 1 9 0.458 6.52 0.0221 2.19e- 3 0.170 #> 10 1 10 0.902 7.43 0.00619 4.32e- 3 0.232 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"function generate n random points Inverse Gaussian distribution user provided, .mean, .shape, .dispersionThe function returns tibble simulation number column x column corresponds n randomly generated points. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"","code":"tidy_inverse_normal( .n = 50, .mean = 1, .shape = 1, .dispersion = 1/.shape, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":".n number randomly generated points want. .mean Must strictly positive. .shape Must strictly positive. .dispersion alternative way specify .shape. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"function uses underlying actuar::rinvgauss(). information please see rinvgauss()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_normal.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Gaussian Distribution Tibble — tidy_inverse_normal","text":"","code":"tidy_inverse_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 4.17 -0.608 0.00152 0 3.37 #> 2 1 2 0.214 -0.490 0.00551 6.89e-12 0 #> 3 1 3 2.80 -0.373 0.0170 1.98e- 6 0.916 #> 4 1 4 0.918 -0.256 0.0445 1.40e- 4 0.306 #> 5 1 5 1.19 -0.139 0.0994 1.22e- 3 0.368 #> 6 1 6 4.31 -0.0219 0.190 4.54e- 3 Inf #> 7 1 7 0.437 0.0952 0.315 1.10e- 2 0.189 #> 8 1 8 0.995 0.212 0.454 2.09e- 2 0.323 #> 9 1 9 0.246 0.329 0.575 3.39e- 2 0.114 #> 10 1 10 2.48 0.447 0.652 4.96e- 2 0.760 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"function generate n random points inverse pareto distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"","code":"tidy_inverse_pareto(.n = 50, .shape = 1, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":".n number randomly generated points want. .shape Must positive. .scale Must positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"function uses underlying actuar::rinvpareto(), underlying p, d, q functions. information please see actuar::rinvpareto()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_pareto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Pareto Distribution Tibble — tidy_inverse_pareto","text":"","code":"tidy_inverse_pareto() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.709 -1.56 4.87e- 1 0 0.0000709 #> 2 1 2 0.841 203. 1.51e-18 0.02 0.0000841 #> 3 1 3 0.267 407. 0 0.0392 0.0000266 #> 4 1 4 1.73 611. 1.52e-19 0.0577 0.000173 #> 5 1 5 0.996 815. 0 0.0755 0.0000996 #> 6 1 6 0.541 1019. 5.69e-19 0.0926 0.0000541 #> 7 1 7 0.261 1223. 6.01e-19 0.109 0.0000260 #> 8 1 8 2.38 1427. 5.59e-20 0.125 0.000238 #> 9 1 9 0.830 1631. 0 0.140 0.0000830 #> 10 1 10 23.5 1835. 2.69e-18 0.155 0.00236 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"function generate n random points weibull distribution user provided, .shape, .scale, .rate, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"","code":"tidy_inverse_weibull( .n = 50, .shape = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":".n number randomly generated points want. .shape Must strictly positive. .rate alternative way specify .scale. .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"function uses underlying actuar::rinvweibull(), underlying p, d, q functions. information please see actuar::rinvweibull()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_inverse_weibull.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Inverse Weibull Distribution Tibble — tidy_inverse_weibull","text":"","code":"tidy_inverse_weibull() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1.54 -2.90 0.000715 0 0.252 #> 2 1 2 19.6 -1.30 0.0359 5.24e-22 0.762 #> 3 1 3 2.06 0.300 0.199 2.29e-11 0.275 #> 4 1 4 0.962 1.90 0.173 8.06e- 8 0.222 #> 5 1 5 0.362 3.50 0.0635 4.79e- 6 0.170 #> 6 1 6 1.06 5.10 0.0398 5.55e- 5 0.228 #> 7 1 7 1.34 6.71 0.0320 2.84e- 4 0.243 #> 8 1 8 1.21 8.31 0.0265 9.12e- 4 0.236 #> 9 1 9 0.492 9.91 0.00490 2.19e- 3 0.186 #> 10 1 10 2.96 11.5 0.00106 4.32e- 3 0.308 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"function takes vector input return kurtosis vector. length vector must least four numbers. kurtosis explains sharpness peak distribution data. ((1/n) * sum(x - mu})^4) / ((()1/n) * sum(x - mu)^2)^2","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"","code":"tidy_kurtosis_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":".x numeric vector length four .","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"kurtosis vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"function return kurtosis vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_kurtosis_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute Kurtosis of a Vector — tidy_kurtosis_vec","text":"","code":"tidy_kurtosis_vec(rnorm(100, 3, 2)) #> [1] 2.700726"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"function generate n random points logistic distribution user provided, .location, .scale, number random simulations produced. function returns tibble simulation number column x column corresonds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"","code":"tidy_logistic(.n = 50, .location = 0, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":".n number randomly generated points want. .location location parameter .scale scale parameter .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"function uses underlying stats::rlogis(), underlying p, d, q functions. information please see stats::rlogis()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_logistic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Logistic Distribution Tibble — tidy_logistic","text":"","code":"tidy_logistic() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 -0.259 -5.78 0.000177 0.5 0.244 #> 2 1 2 1.31 -5.57 0.000556 0.505 1.27 #> 3 1 3 -0.195 -5.37 0.00148 0.510 0.281 #> 4 1 4 -1.00 -5.16 0.00331 0.515 -0.175 #> 5 1 5 -0.0393 -4.95 0.00627 0.520 0.371 #> 6 1 6 0.819 -4.74 0.0101 0.525 0.904 #> 7 1 7 1.77 -4.54 0.0136 0.531 1.69 #> 8 1 8 2.88 -4.33 0.0156 0.536 Inf #> 9 1 9 1.23 -4.12 0.0151 0.541 1.20 #> 10 1 10 2.55 -3.91 0.0124 0.546 3.04 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"function generate n random points lognormal distribution user provided, .meanlog, .sdlog, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"","code":"tidy_lognormal(.n = 50, .meanlog = 0, .sdlog = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":".n number randomly generated points want. .meanlog Mean distribution log scale default 0 .sdlog Standard deviation distribution log scale default 1 .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"function uses underlying stats::rlnorm(), underlying p, d, q functions. information please see stats::rlnorm()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_lognormal.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Lognormal Distribution Tibble — tidy_lognormal","text":"","code":"tidy_lognormal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.187 -1.63 0.00124 0 0.0753 #> 2 1 2 0.406 -1.27 0.00751 0.0000497 0.130 #> 3 1 3 0.187 -0.921 0.0320 0.000690 0.0752 #> 4 1 4 1.31 -0.568 0.0971 0.00261 0.255 #> 5 1 5 0.447 -0.216 0.211 0.00611 0.138 #> 6 1 6 13.9 0.136 0.332 0.0112 Inf #> 7 1 7 0.445 0.489 0.390 0.0179 0.137 #> 8 1 8 0.507 0.841 0.357 0.0258 0.148 #> 9 1 9 0.322 1.19 0.277 0.0350 0.113 #> 10 1 10 2.16 1.55 0.197 0.0451 0.352 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Mixture Data — tidy_mixture_density","title":"Tidy Mixture Data — tidy_mixture_density","text":"Create mixture model data resulting density line plots.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Mixture Data — tidy_mixture_density","text":"","code":"tidy_mixture_density(...)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Mixture Data — tidy_mixture_density","text":"... random data want pass. Example rnorm(50,0,1) something like tidy_normal(.mean = 5, .sd = 1)","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Mixture Data — tidy_mixture_density","text":"list object","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Mixture Data — tidy_mixture_density","text":"function allows make mixture model data. allows produce density data plots data strictly one family one single type distribution given set parameters. example function allow mix say tidy_normal(.mean = 0, .sd = 1) tidy_normal(.mean = 5, .sd = 1) can mix match distributions. output list object three components. Data input_data (random data passed) dist_tbl (tibble passed random data) density_tbl (tibble x y data stats::density()) Plots line_plot - Plots dist_tbl dens_plot - Plots density_tbl Input Functions input_fns - list functions parameters passed function itsefl","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Mixture Data — tidy_mixture_density","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_mixture_density.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Mixture Data — tidy_mixture_density","text":"","code":"output <- tidy_mixture_density(rnorm(100, 0, 1), tidy_normal(.mean = 5, .sd = 1)) output$data #> $dist_tbl #> # A tibble: 150 × 2 #> x y #> #> 1 1 0.968 #> 2 2 0.976 #> 3 3 -0.408 #> 4 4 -0.426 #> 5 5 0.0215 #> 6 6 -0.524 #> 7 7 -0.387 #> 8 8 2.74 #> 9 9 -0.538 #> 10 10 0.269 #> # … with 140 more rows #> #> $dens_tbl #> # A tibble: 150 × 2 #> x y #> #> 1 -5.19 0.0000593 #> 2 -5.09 0.0000862 #> 3 -4.99 0.000124 #> 4 -4.89 0.000176 #> 5 -4.79 0.000246 #> 6 -4.69 0.000342 #> 7 -4.59 0.000467 #> 8 -4.50 0.000634 #> 9 -4.40 0.000849 #> 10 -4.30 0.00112 #> # … with 140 more rows #> #> $input_data #> $input_data$`rnorm(100, 0, 1)` #> [1] 0.96809413 0.97558858 -0.40756517 -0.42627731 0.02154029 -0.52432827 #> [7] -0.38738829 2.74076731 -0.53792547 0.26948111 -1.78445962 2.24643383 #> [13] 1.26493189 1.96092932 -2.24761918 0.48620879 -0.71810854 -1.19139392 #> [19] -0.01817287 2.00278483 -0.29155987 1.00840438 -0.52852330 -0.85089705 #> [25] 0.18483544 1.01974679 -0.54400616 -1.41168242 -0.92258953 0.38635917 #> [31] 1.11937773 -0.09589270 -0.91748327 -0.28551661 0.76816667 0.40025007 #> [37] 1.24358782 0.33517668 -0.79719940 -1.52538655 -2.34885399 -2.66862812 #> [43] 0.30478083 -0.13843533 0.31063402 0.70910967 -1.17595199 -1.01132023 #> [49] 0.82709604 0.35607416 -0.82869311 -0.52556680 -1.03142826 1.10585064 #> [55] -1.69785205 -0.18128867 1.15663490 -0.62948412 1.22625460 -0.91422000 #> [61] 1.00469757 0.25999837 0.10996788 0.55913594 -0.44279002 -0.62840048 #> [67] 1.29919460 -1.31171358 1.73737987 -1.60940430 -1.14286312 -0.38374451 #> [73] -1.25307756 1.63239469 1.09094332 0.89947466 -0.04712680 -0.59406743 #> [79] 1.33382486 0.11651601 -1.39706319 -0.73787351 -2.06394902 2.48544615 #> [85] 1.17771297 -0.67854860 -0.69573897 0.82927667 1.52600077 0.24569111 #> [91] -1.46739032 0.67374103 0.61598918 0.68089456 -0.65829236 -0.37123276 #> [97] -0.81860245 1.11463102 -0.07881766 -1.16943995 #> #> $input_data$`tidy_normal(.mean = 5, .sd = 1)` #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 4.90 1.11 0.000243 0.462 4.90 #> 2 1 2 7.09 1.25 0.000728 0.982 7.09 #> 3 1 3 4.37 1.40 0.00187 0.265 4.37 #> 4 1 4 4.58 1.54 0.00412 0.337 4.58 #> 5 1 5 5.32 1.69 0.00781 0.627 5.32 #> 6 1 6 4.15 1.83 0.0127 0.199 4.15 #> 7 1 7 5.61 1.98 0.0180 0.729 5.61 #> 8 1 8 5.04 2.12 0.0222 0.515 5.04 #> 9 1 9 5.00 2.26 0.0245 0.502 5.00 #> 10 1 10 3.95 2.41 0.0251 0.146 3.95 #> # … with 40 more rows #> #> output$plots #> $line_plot #> #> $dens_plot #> output$input_fns #> [[1]] #> rnorm(100, 0, 1) #> #> [[2]] #> tidy_normal(.mean = 5, .sd = 1) #>"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"auto plotting function take tidy_ distribution function arguments, one plot type, quoted string one following: density quantile probablity qq number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"","code":"tidy_multi_dist_autoplot( .data, .plot_type = \"density\", .line_size = 0.5, .geom_point = FALSE, .point_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .geom_jitter = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":".data data passed function tidy_multi_dist() .plot_type quoted string like 'density' .line_size size param ggplot .geom_point Boolean value TREU/FALSE, FALSE default. TRUE return plot ggplot2::ggeom_point() .point_size point size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .geom_jitter Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_jitter() .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"function spit one following plots: density quantile probability qq","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_dist_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Multi Dist Data — tidy_multi_dist_autoplot","text":"","code":"tn <- tidy_multi_single_dist( .tidy_dist = \"tidy_normal\", .param_list = list( .n = 500, .mean = c(-2, 0, 2), .sd = 1, .num_sims = 5 ) ) tn %>% tidy_multi_dist_autoplot() tn %>% tidy_multi_dist_autoplot(.plot_type = \"qq\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"Generate multiple distributions data tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"","code":"tidy_multi_single_dist(.tidy_dist = NULL, .param_list = list())"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":".tidy_dist type tidy_ distribution want run. can choose one. .param_list must list() object parameters want pass TidyDensity tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"Generate multiple distributions data tidy_ distribution function. allows simulate multiple distributions family order view shapes change parameter changes. can visualize differences however choose.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_multi_single_dist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate Multiple Tidy Distributions of a single type — tidy_multi_single_dist","text":"","code":"tidy_multi_single_dist( .tidy_dist = \"tidy_normal\", .param_list = list( .n = 50, .mean = c(-1, 0, 1), .sd = 1, .num_sims = 3 ) ) #> # A tibble: 450 × 8 #> sim_number dist_name x y dx dy p q #> #> 1 1 Gaussian c(-1, 1) 1 -1.63 -4.37 0.000230 0.264 -1.63 #> 2 1 Gaussian c(-1, 1) 2 0.348 -4.24 0.000612 0.911 0.348 #> 3 1 Gaussian c(-1, 1) 3 -1.29 -4.10 0.00145 0.385 -1.29 #> 4 1 Gaussian c(-1, 1) 4 -0.936 -3.97 0.00303 0.525 -0.936 #> 5 1 Gaussian c(-1, 1) 5 0.853 -3.83 0.00563 0.968 0.853 #> 6 1 Gaussian c(-1, 1) 6 0.408 -3.70 0.00929 0.920 0.408 #> 7 1 Gaussian c(-1, 1) 7 -0.983 -3.56 0.0137 0.507 -0.983 #> 8 1 Gaussian c(-1, 1) 8 0.254 -3.43 0.0180 0.895 0.254 #> 9 1 Gaussian c(-1, 1) 9 -1.52 -3.29 0.0213 0.303 -1.52 #> 10 1 Gaussian c(-1, 1) 10 1.08 -3.16 0.0235 0.981 1.08 #> # … with 440 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"function generate n random points negative binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"","code":"tidy_negative_binomial(.n = 50, .size = 1, .prob = 0.1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":".n number randomly generated points want. .size target number successful trials, dispersion parameter (shape parameter gamma mixing distribution). Must strictly positive, need integer. .prob Probability success trial 0 < .prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"function uses underlying stats::rnbinom(), underlying p, d, q functions. information please see stats::rnbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_negative_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Negative Binomial Distribution Tibble — tidy_negative_binomial","text":"","code":"tidy_negative_binomial() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 3 -8.29 0.000208 0.1 1 #> 2 1 2 0 -7.42 0.000529 0.1 0 #> 3 1 3 5 -6.55 0.00123 0.1 2 #> 4 1 4 10 -5.69 0.00260 0.1 4 #> 5 1 5 12 -4.82 0.00506 0.1 5 #> 6 1 6 10 -3.95 0.00903 0.1 4 #> 7 1 7 0 -3.08 0.0149 0.1 0 #> 8 1 8 4 -2.21 0.0226 0.1 1 #> 9 1 9 11 -1.34 0.0317 0.1 5 #> 10 1 10 8 -0.471 0.0415 0.1 3 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"function generate n random points Gaussian distribution user provided, .mean, .sd - standard deviation number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, dnorm, pnorm qnorm data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"","code":"tidy_normal(.n = 50, .mean = 0, .sd = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":".n number randomly generated points want. .mean mean randomly generated data. .sd standard deviation randomly generated data. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"function uses underlying stats::rnorm(), stats::pnorm(), stats::qnorm() functions generate data given parameters. information please see stats::rnorm()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_normal.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal","text":"","code":"tidy_normal() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 -1.07 -3.14 0.000393 0.142 -1.07 #> 2 1 2 0.877 -3.00 0.00102 0.810 0.877 #> 3 1 3 0.511 -2.87 0.00239 0.695 0.511 #> 4 1 4 -1.51 -2.73 0.00515 0.0661 -1.51 #> 5 1 5 -1.07 -2.60 0.0101 0.143 -1.07 #> 6 1 6 -0.576 -2.46 0.0183 0.282 -0.576 #> 7 1 7 -1.78 -2.33 0.0306 0.0377 -1.78 #> 8 1 8 1.31 -2.19 0.0476 0.906 1.31 #> 9 1 9 -1.66 -2.06 0.0694 0.0485 -1.66 #> 10 1 10 0.743 -1.92 0.0957 0.771 0.743 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"function generate n random points paralogistic distribution user provided, .shape, .rate, .scale number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"","code":"tidy_paralogistic( .n = 50, .shape = 1, .rate = 1, .scale = 1/.rate, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":".n number randomly generated points want. .shape Must strictly positive. .rate alternative way specify .scale .scale Must strictly positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"function uses underlying actuar::rparalogis(), underlying p, d, q functions. information please see actuar::rparalogis()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_paralogistic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic","text":"","code":"tidy_paralogistic() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 2.75 -1.76 0.000797 0 0.198 #> 2 1 2 0.312 -1.35 0.00596 0.0200 0.0181 #> 3 1 3 0.899 -0.937 0.0288 0.0392 0.0564 #> 4 1 4 0.391 -0.528 0.0920 0.0577 0.0231 #> 5 1 5 1.36 -0.119 0.200 0.0755 0.0889 #> 6 1 6 0.332 0.290 0.308 0.0926 0.0194 #> 7 1 7 0.839 0.699 0.354 0.109 0.0524 #> 8 1 8 2.01 1.11 0.321 0.125 0.137 #> 9 1 9 0.207 1.52 0.241 0.140 0.0116 #> 10 1 10 0.0925 1.93 0.163 0.155 0.00455 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"function generate n random points pareto distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"","code":"tidy_pareto(.n = 50, .shape = 10, .scale = 0.1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":".n number randomly generated points want. .shape Must positive. .scale Must positive. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"function uses underlying actuar::rpareto(), underlying p, d, q functions. information please see actuar::rpareto()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Pareto Distribution Tibble — tidy_pareto","text":"","code":"tidy_pareto() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.00558 -0.00860 0.184 0 0.000443 #> 2 1 2 0.000652 -0.00567 2.96 0.844 0.0000405 #> 3 1 3 0.00357 -0.00275 19.1 0.967 0.000276 #> 4 1 4 0.00145 0.000178 52.7 0.992 0.000105 #> 5 1 5 0.0183 0.00310 69.8 0.997 0.00157 #> 6 1 6 0.00139 0.00603 55.1 0.999 0.0000998 #> 7 1 7 0.00122 0.00895 34.6 1.00 0.0000863 #> 8 1 8 0.00169 0.0119 20.1 1.00 0.000124 #> 9 1 9 0.00212 0.0148 10.2 1.00 0.000159 #> 10 1 10 0.0354 0.0177 6.03 1.00 0.00334 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"function generate n random points single parameter pareto distribution user provided, .shape, .min, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"","code":"tidy_pareto1(.n = 50, .shape = 1, .min = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":".n number randomly generated points want. .shape Must positive. .min lower bound support distribution. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"function uses underlying actuar::rpareto1(), underlying p, d, q functions. information please see actuar::rpareto1()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_pareto1.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1","text":"","code":"tidy_pareto1() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 2.33 -2.18 0.000648 0 1.03 #> 2 1 2 1.65 -1.23 0.00800 0 1.02 #> 3 1 3 12.5 -0.278 0.0476 0 1.40 #> 4 1 4 37.3 0.672 0.141 0 10.3 #> 5 1 5 1.48 1.62 0.216 0 1.01 #> 6 1 6 1.24 2.57 0.189 0 1.01 #> 7 1 7 2.38 3.52 0.111 0 1.04 #> 8 1 8 4.36 4.48 0.0629 0 1.09 #> 9 1 9 1.91 5.43 0.0423 0 1.02 #> 10 1 10 3.28 6.38 0.0279 0 1.06 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"function generate n random points Poisson distribution user provided, .lambda, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"","code":"tidy_poisson(.n = 50, .lambda = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":".n number randomly generated points want. .lambda vector non-negative means. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"function uses underlying stats::rpois(), underlying p, d, q functions. information please see stats::rpois()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_poisson.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Poisson Distribution Tibble — tidy_poisson","text":"","code":"tidy_poisson() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 5 -0.921 0.00322 0.368 Inf #> 2 1 2 0 -0.782 0.0113 0.368 0 #> 3 1 3 1 -0.642 0.0323 0.368 0 #> 4 1 4 2 -0.502 0.0752 0.368 1 #> 5 1 5 1 -0.363 0.142 0.368 0 #> 6 1 6 2 -0.223 0.220 0.368 1 #> 7 1 7 1 -0.0835 0.276 0.368 0 #> 8 1 8 3 0.0561 0.286 0.368 1 #> 9 1 9 1 0.196 0.253 0.368 0 #> 10 1 10 0 0.335 0.215 0.368 0 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Random Walk — tidy_random_walk","title":"Tidy Random Walk — tidy_random_walk","text":"Takes data tidy_ distribution function applies random walk calculation either cum_prod cum_sum y.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Random Walk — tidy_random_walk","text":"","code":"tidy_random_walk( .data, .initial_value = 0, .sample = FALSE, .replace = FALSE, .value_type = \"cum_prod\" )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Random Walk — tidy_random_walk","text":".data data passed tidy_ distribution function. .initial_value default 0, can set whatever want. .sample boolean value TRUE/FALSE. default FALSE. set TRUE y value tidy_ distribution function sampled. .replace boolean value TRUE/FALSE. default FALSE. set TRUE .sample set TRUE replace parameter sample function set TRUE. .value_type can take one three different values now. following: \"cum_prod\" - take cumprod y \"cum_sum\" - take cumsum y","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Random Walk — tidy_random_walk","text":"ungrouped tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Random Walk — tidy_random_walk","text":"Monte Carlo simulations first formally designed 1940’s developing nuclear weapons, since heavily used various fields use randomness solve problems potentially deterministic nature. finance, Monte Carlo simulations can useful tool give sense assets certain characteristics might behave future. complex sophisticated financial forecasting methods ARIMA (Auto-Regressive Integrated Moving Average) GARCH (Generalised Auto-Regressive Conditional Heteroskedasticity) attempt model randomness underlying macro factors seasonality volatility clustering, Monte Carlo random walks work surprisingly well illustrating market volatility long results taken seriously.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Random Walk — tidy_random_walk","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Random Walk — tidy_random_walk","text":"","code":"tidy_normal(.sd = .1, .num_sims = 25) %>% tidy_random_walk() #> # A tibble: 1,250 × 8 #> sim_number x y dx dy p q random_walk_value #> #> 1 1 1 0.000858 -0.425 0.00209 0.503 0.000858 0.000858 #> 2 1 2 -0.0531 -0.409 0.00619 0.298 -0.0531 -0.0523 #> 3 1 3 0.0424 -0.392 0.0158 0.664 0.0424 -0.0121 #> 4 1 4 -0.296 -0.375 0.0348 0.00153 -0.296 -0.305 #> 5 1 5 -0.0388 -0.358 0.0657 0.349 -0.0388 -0.332 #> 6 1 6 0.00923 -0.342 0.107 0.537 0.00923 -0.326 #> 7 1 7 -0.0132 -0.325 0.150 0.448 -0.0132 -0.334 #> 8 1 8 0.0568 -0.308 0.184 0.715 0.0568 -0.297 #> 9 1 9 0.155 -0.291 0.197 0.939 0.155 -0.188 #> 10 1 10 0.0659 -0.275 0.194 0.745 0.0659 -0.134 #> # … with 1,240 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"auto-plotting function take tidy_ distribution function arguments regard output visualization. number simulations exceeds 9 legend print. plot subtitle put together attributes table passed function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"","code":"tidy_random_walk_autoplot( .data, .line_size = 1, .geom_rug = FALSE, .geom_smooth = FALSE, .interactive = FALSE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":".data data passed tidy_distribution function like tidy_normal() .line_size size param ggplot .geom_rug Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_rug() .geom_smooth Boolean value TRUE/FALSE, FALSE default. TRUE return use ggplot2::geom_smooth() aes parameter group set FALSE. ensures single smoothing band returned SE also set FALSE. Color set 'black' linetype 'dashed'. .interactive Boolean value TRUE/FALSE, FALSE default. TRUE return interactive plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"ggplot plotly plot.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"function produce simple random walk plot tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_random_walk_autoplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Automatic Plot of Random Walk Data — tidy_random_walk_autoplot","text":"","code":"tidy_normal(.sd = .1, .num_sims = 5) %>% tidy_random_walk(.value_type = \"cum_sum\") %>% tidy_random_walk_autoplot() tidy_normal(.sd = .1, .num_sims = 20) %>% tidy_random_walk(.value_type = \"cum_sum\", .sample = TRUE, .replace = TRUE) %>% tidy_random_walk_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the range statistic — tidy_range_statistic","title":"Get the range statistic — tidy_range_statistic","text":"Takes numeric vector returns back range vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the range statistic — tidy_range_statistic","text":"","code":"tidy_range_statistic(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get the range statistic — tidy_range_statistic","text":".x numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the range statistic — tidy_range_statistic","text":"single number, range statistic","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get the range statistic — tidy_range_statistic","text":"Takes numeric vector returns range vector using diff range functions.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Get the range statistic — tidy_range_statistic","text":"Steven P. Sandeson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_range_statistic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get the range statistic — tidy_range_statistic","text":"","code":"tidy_range_statistic(seq(1:10)) #> [1] 9"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"Takes numeric vector return vector scaled [0,1]","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"","code":"tidy_scale_zero_one_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":".x numeric vector scaled [0,1] inclusive.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"numeric vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"Takes numeric vector return vector scaled [0,1] input vector must numeric. computation fairly straightforward. may helpful trying compare distributions data distribution like beta requires data 0 1 $$y[h] = (x - min(x))/(max(x) - min(x))$$","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_scale_zero_one_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Vector Function Scale to Zero and One — tidy_scale_zero_one_vec","text":"","code":"vec_1 <- rnorm(100, 2, 1) vec_2 <- tidy_scale_zero_one_vec(vec_1) dens_1 <- density(vec_1) dens_2 <- density(vec_2) max_x <- max(dens_1$x, dens_2$x) max_y <- max(dens_1$y, dens_2$y) plot(dens_1, asp = max_y / max_x, main = \"Density vec_1 (Red) and vec_2 (Blue)\", col = \"red\", xlab = \"\", ylab = \"Density of Vec 1 and Vec 2\" ) lines(dens_2, col = \"blue\")"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute Skewness of a Vector — tidy_skewness_vec","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"function takes vector input return skewness vector. length vector must least four numbers. skewness explains 'tailedness' distribution data. ((1/n) * sum(x - mu})^3) / ((()1/n) * sum(x - mu)^2)^(3/2)","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"","code":"tidy_skewness_vec(.x)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":".x numeric vector length four .","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"skewness vector","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"function return skewness vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_skewness_vec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute Skewness of a Vector — tidy_skewness_vec","text":"","code":"tidy_skewness_vec(rnorm(100, 3, 2)) #> [1] -0.1636212"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_stat_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","title":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","text":"function return stat function values given tidy_ distribution output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_stat_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","text":"","code":"tidy_stat_tbl( .data, .x = y, .fns, .return_type = \"vector\", .use_data_table = FALSE, ... )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_stat_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","text":".data input data coming tidy_ distribution function. .x default y can one columns input data. .fns default IQR, can stat function like quantile median etc. .return_type default \"vector\" returns sapply object. .use_data_table default FALSE, TRUE use data.table hood still return tibble. argument set TRUE .return_type parameter ignored. ... Addition function arguments supplied parameters .fns","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_stat_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","text":"return object either sapply lapply tibble based upon user input.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_stat_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","text":"function return value(s) given tidy_ distribution function output chosen column . function work tidy_ distribution functions. currently three different output types function. : \"vector\" - gives sapply() output \"list\" - gives lapply() output, \"tibble\" - returns tibble long format. Currently can pass stat function performs operation vector input. means can pass things like IQR, quantile associated arguments ... portion function. function also default rename value column tibble name function. function also give column name sim_number tibble output corresponding simulation numbers values. sapply lapply outputs column names also give simulation number information making column names like sim_number_1 etc. option .use_data_table can greatly enhance speed calculations performed used still returning tibble. calculations performed turning input data data.table object, performing necessary calculation converting back tibble object.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_stat_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_stat_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Stats of Tidy Distribution — tidy_stat_tbl","text":"","code":"tn <- tidy_normal(.num_sims = 3) p <- c(0.025, 0.25, 0.5, 0.75, 0.95) tidy_stat_tbl(tn, y, quantile, \"vector\", probs = p, na.rm = TRUE) #> sim_number_1 sim_number_2 sim_number_3 #> 2.5% -1.9639261 -2.16592793 -1.931909521 #> 25% -0.7872943 -0.40661213 -0.737074285 #> 50% -0.1080782 -0.06406365 0.001169794 #> 75% 0.6202621 0.50109523 0.716021156 #> 95% 1.4635127 1.30349404 1.730100061 tidy_stat_tbl(tn, y, quantile, \"list\", probs = p) #> $sim_number_1 #> 2.5% 25% 50% 75% 95% #> -1.9639261 -0.7872943 -0.1080782 0.6202621 1.4635127 #> #> $sim_number_2 #> 2.5% 25% 50% 75% 95% #> -2.16592793 -0.40661213 -0.06406365 0.50109523 1.30349404 #> #> $sim_number_3 #> 2.5% 25% 50% 75% 95% #> -1.931909521 -0.737074285 0.001169794 0.716021156 1.730100061 #> tidy_stat_tbl(tn, y, quantile, \"tibble\", probs = p) #> # A tibble: 15 × 3 #> sim_number name quantile #> #> 1 1 2.5% -1.96 #> 2 1 25% -0.787 #> 3 1 50% -0.108 #> 4 1 75% 0.620 #> 5 1 95% 1.46 #> 6 2 2.5% -2.17 #> 7 2 25% -0.407 #> 8 2 50% -0.0641 #> 9 2 75% 0.501 #> 10 2 95% 1.30 #> 11 3 2.5% -1.93 #> 12 3 25% -0.737 #> 13 3 50% 0.00117 #> 14 3 75% 0.716 #> 15 3 95% 1.73 tidy_stat_tbl(tn, y, quantile, .use_data_table = TRUE, probs = p, na.rm = TRUE) #> # A tibble: 15 × 3 #> sim_number name quantile #> #> 1 1 2.5% -1.96 #> 2 1 25% -0.787 #> 3 1 50% -0.108 #> 4 1 75% 0.620 #> 5 1 95% 1.46 #> 6 2 2.5% -2.17 #> 7 2 25% -0.407 #> 8 2 50% -0.0641 #> 9 2 75% 0.501 #> 10 2 95% 1.30 #> 11 3 2.5% -1.93 #> 12 3 25% -0.737 #> 13 3 50% 0.00117 #> 14 3 75% 0.716 #> 15 3 95% 1.73"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated T Distribution Tibble — tidy_t","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"function generate n random points rt distribution user provided, df, ncp, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"","code":"tidy_t(.n = 50, .df = 1, .ncp = 0, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":".n number randomly generated points want. .df Degrees freedom, Inf allowed. .ncp Non-centrality parameter. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"function uses underlying stats::rt(), underlying p, d, q functions. information please see stats::rt()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_t.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated T Distribution Tibble — tidy_t","text":"","code":"tidy_t() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 -0.462 -26.8 2.15e- 4 0.5 -1.25 #> 2 1 2 -0.340 -24.4 3.58e- 3 0.506 -1.24 #> 3 1 3 0.105 -21.9 3.96e- 4 0.513 -1.21 #> 4 1 4 -0.616 -19.5 2.95e-15 0.519 -1.26 #> 5 1 5 -0.414 -17.1 0 0.526 -1.25 #> 6 1 6 4.02 -14.7 0 0.532 -0.979 #> 7 1 7 5.83 -12.2 1.69e-12 0.539 -0.888 #> 8 1 8 0.371 -9.81 2.51e- 3 0.545 -1.19 #> 9 1 9 -0.134 -7.38 8.53e- 3 0.552 -1.23 #> 10 1 10 0.141 -4.96 7.12e- 3 0.558 -1.21 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"function generate n random points uniform distribution user provided, .min .max values, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"","code":"tidy_uniform(.n = 50, .min = 0, .max = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":".n number randomly generated points want. .min lower limit distribution. .max upper limit distribution .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"function uses underlying stats::runif(), underlying p, d, q functions. information please see stats::runif()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_uniform.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Uniform Distribution Tibble — tidy_uniform","text":"","code":"tidy_uniform() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.170 -0.319 0.00234 0 0.126 #> 2 1 2 0.682 -0.284 0.00553 0.0204 0.672 #> 3 1 3 0.417 -0.250 0.0121 0.0408 0.389 #> 4 1 4 0.864 -0.216 0.0249 0.0612 0.865 #> 5 1 5 0.765 -0.182 0.0476 0.0816 0.760 #> 6 1 6 0.222 -0.147 0.0852 0.102 0.181 #> 7 1 7 0.756 -0.113 0.143 0.122 0.750 #> 8 1 8 0.232 -0.0788 0.224 0.143 0.192 #> 9 1 9 0.931 -0.0445 0.330 0.163 0.936 #> 10 1 10 0.220 -0.0102 0.457 0.184 0.179 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"function generate n random points weibull distribution user provided, .shape, .scale, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"","code":"tidy_weibull(.n = 50, .shape = 1, .scale = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":".n number randomly generated points want. .shape Shape parameter defaults 0. .scale Scale parameter defaults 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"function uses underlying stats::rweibull(), underlying p, d, q functions. information please see stats::rweibull()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_weibull.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull","text":"","code":"tidy_weibull() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0.172 -0.889 0.00129 0 0.0358 #> 2 1 2 0.895 -0.786 0.00352 0.0202 0.311 #> 3 1 3 0.839 -0.684 0.00874 0.0400 0.286 #> 4 1 4 0.188 -0.582 0.0197 0.0594 0.0411 #> 5 1 5 2.53 -0.479 0.0402 0.0784 1.57 #> 6 1 6 0.715 -0.377 0.0746 0.0970 0.235 #> 7 1 7 0.679 -0.274 0.126 0.115 0.220 #> 8 1 8 0.0619 -0.172 0.195 0.133 0 #> 9 1 9 0.515 -0.0691 0.277 0.151 0.157 #> 10 1 10 0.442 0.0334 0.362 0.168 0.130 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"function generate n random points zero truncated binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"","code":"tidy_zero_truncated_binomial(.n = 50, .size = 0, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":".n number randomly generated points want. .size Number trials, zero . .prob Probability success trial 0 <= prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"function uses underlying actuar::rztbinom(), underlying p, d, q functions. information please see actuar::rztbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_binomial","text":"","code":"tidy_zero_truncated_binomial() #> Warning: NaNs produced #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 NaN NaN #> 2 1 2 0 -1.18 0.0156 NaN NaN #> 3 1 3 0 -1.13 0.0220 NaN NaN #> 4 1 4 0 -1.08 0.0305 NaN NaN #> 5 1 5 0 -1.03 0.0418 NaN NaN #> 6 1 6 0 -0.983 0.0564 NaN NaN #> 7 1 7 0 -0.932 0.0749 NaN NaN #> 8 1 8 0 -0.882 0.0981 NaN NaN #> 9 1 9 0 -0.832 0.126 NaN NaN #> 10 1 10 0 -0.781 0.161 NaN NaN #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"function generate n random points zero truncated Geometric distribution user provided, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"","code":"tidy_zero_truncated_geometric(.n = 50, .prob = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":".n number randomly generated points want. .prob probability success trial 0 < prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"function uses underlying actuar::rztgeom(), underlying p, d, q functions. information please see actuar::rztgeom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_geometric.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Zero Truncated Geometric Distribution Tibble — tidy_zero_truncated_geometric","text":"","code":"tidy_zero_truncated_geometric() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1 -0.235 0.0109 0 NaN #> 2 1 2 1 -0.184 0.0156 0 NaN #> 3 1 3 1 -0.134 0.0220 0 NaN #> 4 1 4 1 -0.0835 0.0305 0 NaN #> 5 1 5 1 -0.0331 0.0418 0 NaN #> 6 1 6 1 0.0173 0.0564 0 NaN #> 7 1 7 1 0.0677 0.0749 0 NaN #> 8 1 8 1 0.118 0.0981 0 NaN #> 9 1 9 1 0.168 0.126 0 NaN #> 10 1 10 1 0.219 0.161 0 NaN #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"function generate n random points zero truncated binomial distribution user provided, .size, .prob, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"","code":"tidy_zero_truncated_negative_binomial( .n = 50, .size = 0, .prob = 1, .num_sims = 1 )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":".n number randomly generated points want. .size Number trials, zero . .prob Probability success trial 0 <= prob <= 1. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"function uses underlying actuar::rztnbinom(), underlying p, d, q functions. information please see actuar::rztnbinom()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_negative_binomial.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial","text":"","code":"tidy_zero_truncated_binomial() #> Warning: NaNs produced #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 0 -1.23 0.0109 NaN NaN #> 2 1 2 0 -1.18 0.0156 NaN NaN #> 3 1 3 0 -1.13 0.0220 NaN NaN #> 4 1 4 0 -1.08 0.0305 NaN NaN #> 5 1 5 0 -1.03 0.0418 NaN NaN #> 6 1 6 0 -0.983 0.0564 NaN NaN #> 7 1 7 0 -0.932 0.0749 NaN NaN #> 8 1 8 0 -0.882 0.0981 NaN NaN #> 9 1 9 0 -0.832 0.126 NaN NaN #> 10 1 10 0 -0.781 0.161 NaN NaN #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"function generate n random points Zero Truncated Poisson distribution user provided, .lambda, number random simulations produced. function returns tibble simulation number column x column corresponds n randomly generated points, d_, p_ q_ data points well. data returned un-grouped. columns output : sim_number current simulation number. x current value n current simulation. y randomly generated data point. dx x value stats::density() function. dy y value stats::density() function. p values resulting p_ function distribution family. q values resulting q_ function distribution family.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"","code":"tidy_zero_truncated_poisson(.n = 50, .lambda = 1, .num_sims = 1)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":".n number randomly generated points want. .lambda vector non-negative means. .num_sims number randomly generated simulations want.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"tibble randomly generated data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"function uses underlying actuar::rztpois(), underlying p, d, q functions. information please see actuar::rztpois()","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/tidy_zero_truncated_poisson.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble — tidy_zero_truncated_poisson","text":"","code":"tidy_zero_truncated_poisson() #> # A tibble: 50 × 7 #> sim_number x y dx dy p q #> #> 1 1 1 1 0.0786 0.00992 0 1 #> 2 1 2 1 0.177 0.0247 0 1 #> 3 1 3 2 0.276 0.0554 0 1 #> 4 1 4 1 0.375 0.112 0 1 #> 5 1 5 1 0.474 0.204 0 1 #> 6 1 6 1 0.573 0.336 0 1 #> 7 1 7 2 0.672 0.499 0 1 #> 8 1 8 1 0.770 0.668 0 1 #> 9 1 9 1 0.869 0.807 0 1 #> 10 1 10 1 0.968 0.879 0 1 #> # … with 40 more rows"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","title":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","text":"function attempt estimate Bernoulli prob parameter given vector values .x. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated Bernoulli data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","text":"","code":"util_bernoulli_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","text":".x vector data passed function. Must non-negative integers. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","text":"function see given vector .x numeric vector. attempt estimate prob parameter Bernoulli distribution.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Bernoulli Parameters — util_bernoulli_param_estimate","text":"","code":"library(dplyr) library(ggplot2) tb <- tidy_bernoulli(.prob = .1) %>% pull(y) output <- util_bernoulli_param_estimate(tb) output$parameter_tbl #> # A tibble: 1 × 8 #> dist_type samp_size min max mean variance sum_x prob #> #> 1 Bernoulli 50 0 1 0.06 0.0564 3 0.06 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_bernoulli_stats_tbl","title":"Distribution Statistics — util_bernoulli_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_bernoulli_stats_tbl","text":"","code":"util_bernoulli_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_bernoulli_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_bernoulli_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_bernoulli_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_bernoulli_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_bernoulli_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_bernoulli_stats_tbl","text":"","code":"library(dplyr) tidy_bernoulli() %>% util_bernoulli_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_bernoulli\" #> $ function_call \"Bernoulli c(0.1)\" #> $ distribution \"Bernoulli\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 0.1 #> $ mode \"0\" #> $ coeff_var 0.09 #> $ skewness 2.666667 #> $ kurtosis 5.111111 #> $ mad 0.5 #> $ entropy 0.325083 #> $ fisher_information 11.11111 #> $ computed_std_skew 3.096281 #> $ computed_std_kurt 10.58696 #> $ ci_lo 0 #> $ ci_hi 1"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Beta Parameters — util_beta_param_estimate","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"function automatically scale data 0 1 already. means can pass vector like mtcars$mpg worry . function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated beta data. Three different methods shape parameters supplied: Bayes NIST mme EnvStats mme, see EnvStats::ebeta()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"","code":"util_beta_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Beta Parameters — util_beta_param_estimate","text":".x vector data passed function. Must numeric, values must 0 <= x <= 1 .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"function attempt estimate beta shape1 shape2 parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Beta Parameters — util_beta_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_beta_param_estimate(x) #> For the beta distribution, its mean 'mu' should be 0 < mu < 1. The data will #> therefore be scaled to enforce this. output$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape1 shape2 shape…¹ #> #> 1 Beta 32 10.4 33.9 0.412 0.0658 Bayes 13.2 18.8 0.702 #> 2 Beta 32 10.4 33.9 0.412 0.0658 NIST_MME 1.11 1.58 0.702 #> 3 Beta 32 10.4 33.9 0.412 0.0658 EnvStats… 1.16 1.65 0.702 #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot() tb <- rbeta(50, 2.5, 1.4) util_beta_param_estimate(tb)$parameter_tbl #> There was no need to scale the data. #> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape1 shape2 shape…¹ #> #> 1 Beta 50 0.196 0.989 0.629 0.0350 Bayes 31.4 18.6 1.69 #> 2 Beta 50 0.196 0.989 0.629 0.0350 NIST_MME 3.57 2.11 1.69 #> 3 Beta 50 0.196 0.989 0.629 0.0350 EnvStats… 3.65 2.16 1.69 #> # … with abbreviated variable name ¹​shape_ratio"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_beta_stats_tbl","title":"Distribution Statistics — util_beta_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_beta_stats_tbl","text":"","code":"util_beta_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_beta_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_beta_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_beta_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_beta_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_beta_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_beta_stats_tbl","text":"","code":"library(dplyr) tidy_beta() %>% util_beta_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_beta\" #> $ function_call \"Beta c(1, 1, 0)\" #> $ distribution \"Beta\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0.5 #> $ mode \"undefined\" #> $ range \"0 to 1\" #> $ std_dv 0.2886751 #> $ coeff_var 0.5773503 #> $ skewness 0 #> $ kurtosis NA #> $ computed_std_skew 0.06575886 #> $ computed_std_kurt 1.756644 #> $ ci_lo 0.06993433 #> $ ci_hi 0.9717098"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Binomial Parameters — util_binomial_param_estimate","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"function check see given vector .x either numeric vector factor vector least two levels cause error function abort. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated binomial data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"","code":"util_binomial_param_estimate(.x, .size = NULL, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":".x vector data passed function. Must numeric, values must 0 <= x <= 1 .size Number trials, zero . .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"function attempt estimate binomial p_hat size parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Binomial Parameters — util_binomial_param_estimate","text":"","code":"library(dplyr) library(ggplot2) tb <- rbinom(50, 1, .1) output <- util_binomial_param_estimate(tb) output$parameter_tbl #> # A tibble: 1 × 10 #> dist_type samp_size min max mean variance method prob size shape…¹ #> #> 1 Binomial 50 0 1 0.12 0.108 EnvStats_M… 0.12 50 0.0024 #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_binomial_stats_tbl","title":"Distribution Statistics — util_binomial_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_binomial_stats_tbl","text":"","code":"util_binomial_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_binomial_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_binomial_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_binomial_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_binomial_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_binomial_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_binomial_stats_tbl","text":"","code":"library(dplyr) tidy_binomial() %>% util_binomial_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_binomial\" #> $ function_call \"Binomial c(0, 1)\" #> $ distribution \"Binomial\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ mode_lower 0 #> $ mode_upper 1 #> $ range \"0 to 0\" #> $ std_dv 0 #> $ coeff_var NaN #> $ skewness -Inf #> $ kurtosis NaN #> $ computed_std_skew NaN #> $ computed_std_kurt NaN #> $ ci_lo 0 #> $ ci_hi 0"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Cauchy Parameters — util_cauchy_param_estimate","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated cauchy data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"","code":"util_cauchy_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"function attempt estimate cauchy location scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Cauchy Parameters — util_cauchy_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- tidy_cauchy(.location = 0, .scale = 1)$y output <- util_cauchy_param_estimate(x) output$parameter_tbl #> # A tibble: 1 × 8 #> dist_type samp_size min max method location scale ratio #> #> 1 Cauchy 50 -119. 40.6 MASS -0.0599 2.01 -0.0298 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_cauchy_stats_tbl","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"","code":"util_cauchy_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_cauchy_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_cauchy_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_cauchy_stats_tbl","text":"","code":"library(dplyr) tidy_cauchy() %>% util_cauchy_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_cauchy\" #> $ function_call \"Cauchy c(0, 1)\" #> $ distribution \"Cauchy\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean \"undefined\" #> $ median 0 #> $ mode 0 #> $ std_dv \"undefined\" #> $ coeff_var \"undefined\" #> $ skewness 0 #> $ kurtosis \"undefined\" #> $ computed_std_skew 3.338946 #> $ computed_std_kurt 16.69811 #> $ ci_lo -3.869178 #> $ ci_hi 13.64284"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_chisquare_stats_tbl","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"","code":"util_chisquare_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_chisquare_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_chisquare_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_chisquare_stats_tbl","text":"","code":"library(dplyr) tidy_chisquare() %>% util_chisquare_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_chisquare\" #> $ function_call \"Chisquare c(1, 1)\" #> $ distribution \"Chisquare\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ median 0.3333333 #> $ mode \"undefined\" #> $ std_dv 1.414214 #> $ coeff_var 1.414214 #> $ skewness 2.828427 #> $ kurtosis 15 #> $ computed_std_skew 0.9979738 #> $ computed_std_kurt 2.820907 #> $ ci_lo 0.009561891 #> $ ci_hi 7.009665"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Exponential Parameters — util_exponential_param_estimate","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"function attempt estimate exponential rate parameter given vector values. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated exponential data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"","code":"util_exponential_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":".x vector data passed function. Must numeric. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"function see given vector .x numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Exponential Parameters — util_exponential_param_estimate","text":"","code":"library(dplyr) library(ggplot2) te <- tidy_exponential(.rate = .1) %>% pull(y) output <- util_exponential_param_estimate(te) output$parameter_tbl #> # A tibble: 1 × 8 #> dist_type samp_size min max mean variance method rate #> #> 1 Exponential 50 0.112 42.8 12.4 120. NIST_MME 0.0805 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_exponential_stats_tbl","title":"Distribution Statistics — util_exponential_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_exponential_stats_tbl","text":"","code":"util_exponential_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_exponential_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_exponential_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_exponential_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_exponential_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_exponential_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_exponential_stats_tbl","text":"","code":"library(dplyr) tidy_exponential() %>% util_exponential_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_exponential\" #> $ function_call \"Exponential c(1)\" #> $ distribution \"Exponential\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ median 0.6931472 #> $ mode 1 #> $ range \"1 to Inf\" #> $ std_dv 1 #> $ coeff_var 1 #> $ skewness 2 #> $ kurtosis 9 #> $ computed_std_skew 1.018969 #> $ computed_std_kurt 3.549073 #> $ ci_lo 0.04006036 #> $ ci_hi 2.808457"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_f_stats_tbl","title":"Distribution Statistics — util_f_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_f_stats_tbl","text":"","code":"util_f_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_f_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_f_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_f_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_f_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_f_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_f_stats_tbl","text":"","code":"library(dplyr) tidy_f() %>% util_f_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_f\" #> $ function_call \"F Distribution c(1, 1, 0)\" #> $ distribution \"f\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean \"undefined\" #> $ median \"Not computed\" #> $ mode \"undefined\" #> $ std_dv \"undefined\" #> $ coeff_var \"undefined\" #> $ skewness \"undefined\" #> $ kurtosis \"Not computed\" #> $ computed_std_skew 6.799377 #> $ computed_std_kurt 47.48836 #> $ ci_lo 0.01065216 #> $ ci_hi 66.38577"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Gamma Parameters — util_gamma_param_estimate","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"function attempt estimate gamma shape scale parameters given vector values. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated gamma data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"","code":"util_gamma_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":".x vector data passed function. Must numeric. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"function see given vector .x numeric vector.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Gamma Parameters — util_gamma_param_estimate","text":"","code":"library(dplyr) library(ggplot2) tg <- tidy_gamma(.shape = 1, .scale = .3) %>% pull(y) output <- util_gamma_param_estimate(tg) output$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean variance method shape scale shape…¹ #> #> 1 Gamma 50 0.00231 1.04 0.295 0.279 NIST_MME 1.11 0.264 4.22 #> 2 Gamma 50 0.00231 1.04 0.295 0.279 EnvStats… 1.09 0.264 4.13 #> 3 Gamma 50 0.00231 1.04 0.295 0.279 EnvStats… 1.06 0.264 4.01 #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_gamma_stats_tbl","title":"Distribution Statistics — util_gamma_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_gamma_stats_tbl","text":"","code":"util_gamma_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_gamma_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_gamma_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_gamma_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_gamma_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_gamma_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_gamma_stats_tbl","text":"","code":"library(dplyr) tidy_gamma() %>% util_gamma_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_gamma\" #> $ function_call \"Gamma c(1, 0.3)\" #> $ distribution \"Gamma\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ mode 0 #> $ range \"0 to Inf\" #> $ std_dv 1 #> $ coeff_var 1 #> $ skewness 2 #> $ kurtosis 9 #> $ computed_std_skew 1.104969 #> $ computed_std_kurt 3.450766 #> $ ci_lo 0.004632404 #> $ ci_hi 0.8097946"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Geometric Parameters — util_geometric_param_estimate","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"function attempt estimate geometric prob parameter given vector values .x. function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated geometric data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"","code":"util_geometric_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":".x vector data passed function. Must non-negative integers. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"function see given vector .x numeric vector. attempt estimate prob parameter geometric distribution.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Geometric Parameters — util_geometric_param_estimate","text":"","code":"library(dplyr) library(ggplot2) tg <- tidy_geometric(.prob = .1) %>% pull(y) output <- util_geometric_param_estimate(tg) output$parameter_tbl #> # A tibble: 2 × 9 #> dist_type samp_size min max mean variance sum_x method shape #> #> 1 Geometric 50 0 41 11.1 101. 554 EnvStats_MME 0.0828 #> 2 Geometric 50 0 41 11.1 101. 554 EnvStats_MVUE 0.0813 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_geometric_stats_tbl","title":"Distribution Statistics — util_geometric_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_geometric_stats_tbl","text":"","code":"util_geometric_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_geometric_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_geometric_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_geometric_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_geometric_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_geometric_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_geometric_stats_tbl","text":"","code":"library(dplyr) tidy_geometric() %>% util_geometric_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_geometric\" #> $ function_call \"Geometric c(1)\" #> $ distribution \"Geometric\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ mode 0 #> $ range \"0 to Inf\" #> $ std_dv 0 #> $ coeff_var 0 #> $ skewness Inf #> $ kurtosis Inf #> $ computed_std_skew NaN #> $ computed_std_kurt NaN #> $ ci_lo 0 #> $ ci_hi 0"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"function attempt estimate geometric prob parameter given vector values .x. Estimate m, number white balls urn, m+n, total number balls urn, hypergeometric distribution.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"","code":"util_hypergeometric_param_estimate( .x, .m = NULL, .total = NULL, .k, .auto_gen_empirical = TRUE )"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":".x non-negative integer indicating number white balls sample size .k drawn without replacement urn. missing, undefined infinite values. .m Non-negative integer indicating number white balls urn. must supply .m .total, . missing values. .total positive integer indicating total number balls urn (.e., m+n). must supply .m .total, . missing values. .k positive integer indicating number balls drawn without replacement urn. missing values. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"function see given vector .x numeric integer. attempt estimate prob parameter geometric distribution. Missing (NA), undefined (NaN), infinite (Inf, -Inf) values allowed. Let .x observation hypergeometric distribution parameters .m = M, .n = N, .k = K. R nomenclature, .x represents number white balls drawn sample .k balls drawn without replacement urn containing .m white balls .n black balls. total number balls urn thus .m + .n. Denote total number balls T = .m + .n","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Hypergeometric Parameters — util_hypergeometric_param_estimate","text":"","code":"library(dplyr) library(ggplot2) th <- rhyper(10, 20, 30, 5) output <- util_hypergeometric_param_estimate(th, .total = 50, .k = 5) output$parameter_tbl #> # A tibble: 2 × 5 #> dist_type samp_size method m total #> #> 1 Hypergeometric 10 EnvStats_MLE 10.2 NA #> 2 Hypergeometric 10 EnvStats_MVUE 10 50 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_hypergeometric_stats_tbl","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"","code":"util_hypergeometric_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_hypergeometric_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_hypergeometric_stats_tbl","text":"","code":"library(dplyr) tidy_hypergeometric() %>% util_hypergeometric_stats_tbl() %>% glimpse() #> Warning: NaNs produced #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_hypergeometric\" #> $ function_call \"Hypergeometric c(0, 0, 0)\" #> $ distribution \"Hypergeometric\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean NaN #> $ mode_lower -0.5 #> $ mode_upper 0.5 #> $ range \"0 to Inf\" #> $ std_dv NaN #> $ coeff_var NaN #> $ skewness NaN #> $ kurtosis NaN #> $ computed_std_skew NaN #> $ computed_std_kurt NaN #> $ ci_lo 0 #> $ ci_hi 0"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Logistic Parameters — util_logistic_param_estimate","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated logistic data. Three different methods shape parameters supplied: MLE MME MMUE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"","code":"util_logistic_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"function attempt estimate logistic location scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Logistic Parameters — util_logistic_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_logistic_param_estimate(x) output$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean basic_scale method locat…¹ scale shape…² #> #> 1 Logistic 32 10.4 33.9 20.1 3.27 EnvSt… 20.1 3.27 6.14 #> 2 Logistic 32 10.4 33.9 20.1 3.27 EnvSt… 20.1 3.32 6.05 #> 3 Logistic 32 10.4 33.9 20.1 3.27 EnvSt… 20.1 12.6 1.60 #> # … with abbreviated variable names ¹​location, ²​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot() t <- rlogis(50, 2.5, 1.4) util_logistic_param_estimate(t)$parameter_tbl #> # A tibble: 3 × 10 #> dist_type samp_size min max mean basic_scale method locat…¹ scale shape…² #> #> 1 Logistic 50 -3.77 9.27 3.03 1.35 EnvSt… 3.03 1.35 2.24 #> 2 Logistic 50 -3.77 9.27 3.03 1.35 EnvSt… 3.03 1.37 2.22 #> 3 Logistic 50 -3.77 9.27 3.03 1.35 EnvSt… 3.03 1.86 1.63 #> # … with abbreviated variable names ¹​location, ²​shape_ratio"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_logistic_stats_tbl","title":"Distribution Statistics — util_logistic_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_logistic_stats_tbl","text":"","code":"util_logistic_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_logistic_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_logistic_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_logistic_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_logistic_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_logistic_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_logistic_stats_tbl","text":"","code":"library(dplyr) tidy_logistic() %>% util_logistic_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_logistic\" #> $ function_call \"Logistic c(0, 1)\" #> $ distribution \"Logistic\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ mode_lower 0 #> $ range \"0 to Inf\" #> $ std_dv 1.813799 #> $ coeff_var 3.289868 #> $ skewness 0 #> $ kurtosis 1.2 #> $ computed_std_skew -0.244126 #> $ computed_std_kurt 3.542863 #> $ ci_lo -3.169252 #> $ ci_hi 3.057175"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Lognormal Parameters — util_lognormal_param_estimate","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated lognormal data. Three different methods shape parameters supplied: mme, see EnvStats::elnorm() mle, see EnvStats::elnorm()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"","code":"util_lognormal_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"function attempt estimate lognormal meanlog log sd parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Lognormal Parameters — util_lognormal_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_lognormal_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mean_log sd_log shape_ratio #> #> 1 Lognormal 32 10.4 33.9 EnvStats_MVUE 2.96 0.298 9.93 #> 2 Lognormal 32 10.4 33.9 EnvStats_MME 2.96 0.293 10.1 output$combined_data_tbl %>% tidy_combined_autoplot() tb <- tidy_lognormal(.meanlog = 2, .sdlog = 1) %>% pull(y) util_lognormal_param_estimate(tb)$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mean_log sd_log shape_ratio #> #> 1 Lognormal 50 0.645 98.5 EnvStats_MVUE 2.02 1.25 1.62 #> 2 Lognormal 50 0.645 98.5 EnvStats_MME 2.02 1.24 1.64"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_lognormal_stats_tbl","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"","code":"util_lognormal_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_lognormal_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_lognormal_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_lognormal_stats_tbl","text":"","code":"library(dplyr) tidy_lognormal() %>% util_lognormal_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 18 #> $ tidy_function \"tidy_lognormal\" #> $ function_call \"Lognormal c(0, 1)\" #> $ distribution \"Lognormal\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1.648721 #> $ median 1 #> $ mode 0.3678794 #> $ range \"0 to Inf\" #> $ std_dv 2.161197 #> $ coeff_var 1.310832 #> $ skewness 6.184877 #> $ kurtosis 113.9364 #> $ computed_std_skew 5.231007 #> $ computed_std_kurt 33.27799 #> $ ci_lo 0.1049607 #> $ ci_hi 5.759606"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated negative binomial data. Two different methods shape parameters supplied: MLE/MME MMUE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"","code":"util_negative_binomial_param_estimate(.x, .size, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":".x vector data passed function. .size size parameter. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"function attempt estimate negative binomial size prob parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Negative Binomial Parameters — util_negative_binomial_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- as.integer(mtcars$mpg) output <- util_negative_binomial_param_estimate(x, .size = 1) output$parameter_tbl #> # A tibble: 2 × 9 #> dist_type samp_size min max mean method size prob shape…¹ #> #> 1 Negative Binomial 32 10 33 19.7 EnvStats_M… 32 0.0483 662 #> 2 Negative Binomial 32 10 33 19.7 EnvStats_M… 32 0.0469 682. #> # … with abbreviated variable name ¹​shape_ratio output$combined_data_tbl %>% tidy_combined_autoplot() t <- rnbinom(50, 1, .1) util_negative_binomial_param_estimate(t, .size = 1)$parameter_tbl #> # A tibble: 2 × 9 #> dist_type samp_size min max mean method size prob shape…¹ #> #> 1 Negative Binomial 50 0 44 10.2 EnvStats_M… 50 0.0891 561 #> 2 Negative Binomial 50 0 44 10.2 EnvStats_M… 50 0.0875 571. #> # … with abbreviated variable name ¹​shape_ratio"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_negative_binomial_stats_tbl","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"","code":"util_negative_binomial_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_negative_binomial_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_negative_binomial_stats_tbl","text":"","code":"library(dplyr) tidy_negative_binomial() %>% util_negative_binomial_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_negative_binomial\" #> $ function_call \"Negative Binomial c(1, 0.1)\" #> $ distribution \"Negative Binomial\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 0.1111111 #> $ mode_lower 0 #> $ range \"0 to Inf\" #> $ std_dv 0.3513642 #> $ coeff_var 0.1234568 #> $ skewness 3.478505 #> $ kurtosis 14.1 #> $ computed_std_skew 1.579481 #> $ computed_std_kurt 5.00942 #> $ ci_lo 0 #> $ ci_hi 49.975"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated normal data. Three different methods shape parameters supplied: MLE/MME MVUE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"","code":"util_normal_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"function attempt estimate normal gaussian mean standard deviation parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Normal Gaussian Parameters — util_normal_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_normal_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mu stan_dev shape_ratio #> #> 1 Gaussian 32 10.4 33.9 EnvStats_MME_MLE 20.1 5.93 3.39 #> 2 Gaussian 32 10.4 33.9 EnvStats_MVUE 20.1 6.03 3.33 output$combined_data_tbl %>% tidy_combined_autoplot() t <- rnorm(50, 0, 1) util_normal_param_estimate(t)$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method mu stan_dev shape_ratio #> #> 1 Gaussian 50 -2.09 2.19 EnvStats_MME_MLE -0.109 1.00 -0.109 #> 2 Gaussian 50 -2.09 2.19 EnvStats_MVUE -0.109 1.01 -0.108"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_normal_stats_tbl","title":"Distribution Statistics — util_normal_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_normal_stats_tbl","text":"","code":"util_normal_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_normal_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_normal_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_normal_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_normal_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_normal_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_normal_stats_tbl","text":"","code":"library(dplyr) tidy_normal() %>% util_normal_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_gaussian\" #> $ function_call \"Gaussian c(0, 1)\" #> $ distribution \"Gaussian\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ median 0.2399192 #> $ mode 0 #> $ std_dv 1 #> $ coeff_var Inf #> $ skewness 0 #> $ kurtosis 3 #> $ computed_std_skew -0.2225466 #> $ computed_std_kurt 2.929565 #> $ ci_lo -1.859047 #> $ ci_hi 1.949315"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Pareto Parameters — util_pareto_param_estimate","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated pareto data. Two different methods shape parameters supplied: LSE MLE","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"","code":"util_pareto_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"function attempt estimate pareto shape scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Pareto Parameters — util_pareto_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- mtcars$mpg output <- util_pareto_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method shape scale shape_ratio #> #> 1 Pareto 32 10.4 33.9 LSE 13.7 2.86 4.79 #> 2 Pareto 32 10.4 33.9 MLE 10.4 1.62 6.40 output$combined_data_tbl %>% tidy_combined_autoplot() t <- tidy_pareto(50, 1, 1) %>% pull(y) util_pareto_param_estimate(t)$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method shape scale shape_ratio #> #> 1 Pareto 50 0.0877 71.3 LSE 0.248 0.688 0.361 #> 2 Pareto 50 0.0877 71.3 MLE 0.0877 0.405 0.217"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_pareto_stats_tbl","title":"Distribution Statistics — util_pareto_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_pareto_stats_tbl","text":"","code":"util_pareto_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_pareto_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_pareto_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_pareto_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_pareto_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_pareto_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_pareto_stats_tbl","text":"","code":"library(dplyr) tidy_pareto() %>% util_pareto_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_pareto\" #> $ function_call \"Pareto c(10, 0.1)\" #> $ distribution \"Pareto\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0.1111111 #> $ mode_lower 0.1 #> $ range \"0 to Inf\" #> $ std_dv 0.0124226 #> $ coeff_var 0.000154321 #> $ skewness 2.811057 #> $ kurtosis 14.82857 #> $ computed_std_skew 1.351763 #> $ computed_std_kurt 4.764217 #> $ ci_lo 0.0004912303 #> $ ci_hi 0.0368343"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Poisson Parameters — util_poisson_param_estimate","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated poisson data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"","code":"util_poisson_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"function attempt estimate pareto lambda parameter given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Poisson Parameters — util_poisson_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- as.integer(mtcars$mpg) output <- util_poisson_param_estimate(x) output$parameter_tbl #> # A tibble: 1 × 6 #> dist_type samp_size min max method lambda #> #> 1 Posson 32 10 33 MLE 19.7 output$combined_data_tbl %>% tidy_combined_autoplot() t <- rpois(50, 5) util_poisson_param_estimate(t)$parameter_tbl #> # A tibble: 1 × 6 #> dist_type samp_size min max method lambda #> #> 1 Posson 50 0 9 MLE 5.02"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_poisson_stats_tbl","title":"Distribution Statistics — util_poisson_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_poisson_stats_tbl","text":"","code":"util_poisson_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_poisson_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_poisson_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_poisson_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_poisson_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_poisson_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_poisson_stats_tbl","text":"","code":"library(dplyr) tidy_poisson() %>% util_poisson_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_poisson\" #> $ function_call \"Poisson c(1)\" #> $ distribution \"Poisson\" #> $ distribution_type \"discrete\" #> $ points 50 #> $ simulations 1 #> $ mean 1 #> $ mode 1 #> $ range \"0 to Inf\" #> $ std_dv 1 #> $ coeff_var 1 #> $ skewness 1 #> $ kurtosis 4 #> $ computed_std_skew 0.5753952 #> $ computed_std_kurt 2.484442 #> $ ci_lo 0 #> $ ci_hi 3"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_t_stats_tbl","title":"Distribution Statistics — util_t_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_t_stats_tbl","text":"","code":"util_t_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_t_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_t_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_t_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_t_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_t_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_t_stats_tbl","text":"","code":"library(dplyr) tidy_t() %>% util_t_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 17 #> $ tidy_function \"tidy_t\" #> $ function_call \"T Distribution c(1, 0)\" #> $ distribution \"t\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0 #> $ median 0 #> $ mode 0 #> $ std_dv \"undefined\" #> $ coeff_var \"undefined\" #> $ skewness 0 #> $ kurtosis \"undefined\" #> $ computed_std_skew 3.492746 #> $ computed_std_kurt 16.59944 #> $ ci_lo -6.492515 #> $ ci_hi 26.14414"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Uniform Parameters — util_uniform_param_estimate","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated uniform data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"","code":"util_uniform_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"function attempt estimate uniform min max parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Uniform Parameters — util_uniform_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- tidy_uniform(.min = 1, .max = 3)$y output <- util_uniform_param_estimate(x) output$parameter_tbl #> # A tibble: 2 × 8 #> dist_type samp_size min max method min_est max_est ratio #> #> 1 Uniform 50 1.01 2.93 NIST_MME 1.06 2.98 0.355 #> 2 Uniform 50 1.01 2.93 NIST_MLE 1 3 0.333 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_uniform_stats_tbl","title":"Distribution Statistics — util_uniform_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_uniform_stats_tbl","text":"","code":"util_uniform_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_uniform_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_uniform_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_uniform_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_uniform_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_uniform_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_uniform_stats_tbl","text":"","code":"library(dplyr) tidy_uniform() %>% util_uniform_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 16 #> $ tidy_function \"tidy_uniform\" #> $ function_call \"Uniform c(0, 1)\" #> $ distribution \"Uniform\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 0.5 #> $ median 0.5 #> $ std_dv 0.2886751 #> $ coeff_var 0.5773503 #> $ skewness 0 #> $ kurtosis 1.8 #> $ computed_std_skew 0.2448167 #> $ computed_std_kurt 1.741354 #> $ ci_lo 0.01871572 #> $ ci_hi 0.9429315"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate Weibull Parameters — util_weibull_param_estimate","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"function return list output default, parameter .auto_gen_empirical set TRUE empirical data given parameter .x run tidy_empirical() function combined estimated weibull data.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"","code":"util_weibull_param_estimate(.x, .auto_gen_empirical = TRUE)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":".x vector data passed function. .auto_gen_empirical boolean value TRUE/FALSE default set TRUE. automatically create tidy_empirical() output .x parameter use tidy_combine_distributions(). user can plot data using $combined_data_tbl function output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"tibble/list","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"function attempt estimate weibull shape scale parameters given vector values.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_param_estimate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate Weibull Parameters — util_weibull_param_estimate","text":"","code":"library(dplyr) library(ggplot2) x <- tidy_weibull(.shape = 1, .scale = 2)$y output <- util_weibull_param_estimate(x) output$parameter_tbl #> # A tibble: 1 × 8 #> dist_type samp_size min max method shape scale shape_ratio #> #> 1 Weibull 50 0.0286 8.68 NIST 1.00 1.96 0.510 output$combined_data_tbl %>% tidy_combined_autoplot()"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":null,"dir":"Reference","previous_headings":"","what":"Distribution Statistics — util_weibull_stats_tbl","title":"Distribution Statistics — util_weibull_stats_tbl","text":"Returns distribution statistics tibble.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Distribution Statistics — util_weibull_stats_tbl","text":"","code":"util_weibull_stats_tbl(.data)"},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Distribution Statistics — util_weibull_stats_tbl","text":".data data passed tidy_ distribution function.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Distribution Statistics — util_weibull_stats_tbl","text":"tibble","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Distribution Statistics — util_weibull_stats_tbl","text":"function take tibble returns statistics given type tidy_ distribution. required data passed tidy_ distribution function.","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Distribution Statistics — util_weibull_stats_tbl","text":"Steven P. Sanderson II, MPH","code":""},{"path":"https://www.spsanderson.com/TidyDensity/reference/util_weibull_stats_tbl.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Distribution Statistics — util_weibull_stats_tbl","text":"","code":"library(dplyr) tidy_weibull() %>% util_weibull_stats_tbl() %>% glimpse() #> Rows: 1 #> Columns: 16 #> $ tidy_function \"tidy_weibull\" #> $ function_call \"Weibull c(1, 1)\" #> $ distribution \"Weibull\" #> $ distribution_type \"continuous\" #> $ points 50 #> $ simulations 1 #> $ mean 1.222403 #> $ median 0.8184428 #> $ mode 0 #> $ range \"0 to Inf\" #> $ std_dv 1.128565 #> $ coeff_var 1.27366 #> $ computed_std_skew 1.152611 #> $ computed_std_kurt 3.774209 #> $ ci_lo 0.05912578 #> $ ci_hi 3.336329"},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-development-version","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity (development version)","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-development-version","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity (development version)","text":"Fix #302 - Add function tidy_bernoulli() Fix #304 - Add function util_bernoulli_param_estimate() Fix #305 - Add function util_bernoulli_stats_tbl()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-development-version","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity (development version)","text":"Fix #291 - Update tidy_stat_tbl() fix tibble output longer ignores passed arguments fix data.table directly pass … arguments. Fix #295 - Drop warning message passing arguments .use_data_table = TRUE Fix #303 - Add tidy_bernoulli() autoplot. Fix #299 - Update tidy_stat_tbl() Fix #309 - Add function internal use drop dependency stringr. Function dist_type_extractor() used several functions library. Fix #310 - Update combine-multi-dist use dist_type_extractor() Fix #311 - Update util_dist_stats_tbl() functions use dist_type_extractor() Fix #316 - Update autoplot functions tidy_bernoulli() Fix #312 - Update random walk function use dist_type_extractor() Fix #314 - Update tidy_stat_tbl() use dist_type_extractor()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-123","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.2.3","title":"TidyDensity 1.2.3","text":"CRAN release: 2022-10-04","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-2-3","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.2.3","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-2-3","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.2.3","text":"Fix #237 - Add function bootstrap_density_augment() Fix #238 - Add functions bootstrap_p_vec() bootstrap_p_augment() Fix #239 - Add functions bootstrap_q_vec() bootstrap_q_augment() Fix #256 #257 #258 #260 #265 #266 #267 #268 - Add functions cmean() chmean() cgmean() cmedian() csd() ckurtosis() cskewness() cvar() Fix #250 - Add function bootstrap_stat_plot() Fix #276 - Add function tidy_stat_tbl() Fix #281 adds parameter .user_data_table set FALSE default. set TRUE use [data.table::melt()] underlying work speeding output benchmark test regular tibble 72 seconds data.table. 15 seconds.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-2-3","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.2.3","text":"Fix #242 - Fix prop check tidy_bootstrap() Fix #247 - Add attributes bootstrap_density_augment() output.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-122","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.2.2","title":"TidyDensity 1.2.2","text":"CRAN release: 2022-08-10","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-2-2","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.2.2","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-2-2","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.2.2","text":"Fix #229 - Add tidy_normal() list tested distributions. Add AIC linear model metric, add stats::ks.test() metric.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-2-2","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.2.2","text":"Fix #228 - Add ks.test distribution comparison. Fix #227 - Add AIC normal distribution comparison.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-121","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.2.1","title":"TidyDensity 1.2.1","text":"CRAN release: 2022-07-19","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-2-1","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.2.1","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-2-1","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.2.1","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvments-1-2-1","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvments","title":"TidyDensity 1.2.1","text":"Fix #210 - Fix param_grid order internal affected attributes thus display order parameters. Fix #211 - Add High Low CI tidy_distribution_summary_tbl() Fix #213 - Use purrr::compact() list distributions passed order prevent issue occurring #212 Fix #212 - Make tidy_distribution_comparison() robust terms handling bad erroneous data. Fix #216 - Add attribute “tibble_type” tidy_multi_single_dist() helps work functions like tidy_random_walk()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-120","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.2.0","title":"TidyDensity 1.2.0","text":"CRAN release: 2022-06-08","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-2-0","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.2.0","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-2-0","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.2.0","text":"Fix #181 - Add functions color_blind() td_scale_fill_colorblind() td_scale_color_colorblind() Fix #187 - Add functions ci_lo() ci_hi() Fix #189 - Add function tidy_bootstrap() Fix #190 - Add function bootstrap_unnest_tbl() Fix #202 - Add function tidy_distribution_comparison()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-2-0","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.2.0","text":"Fix #176 - Update _autoplot functions include cumulative mean MCMC chart taking advantage .num_sims parameter tidy_ distribution functions. Fix #184 - Update tidy_empirical() add parameter .distribution_type Fix #183 - tidy_empirical() now plotted _autoplot functions. Fix #188 - Add .num_sims parameter tidy_empirical() Fix #196 - Add ci_lo() ci_hi() stats tbl functions. Fix #201 - Correct attribute distribution_family_type discrete tidy_geometric()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-110","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.1.0","title":"TidyDensity 1.1.0","text":"CRAN release: 2022-05-06","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-1-0","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.1.0","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-1-0","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.1.0","text":"Fix #119 - Add function tidy_four_autoplot() - auto plot density, qq, quantile probability plots single graph. Fix #125 - Add function util_weibull_param_estimate() Fix #126 - Add function util_uniform_param_estimate() Fix #127 - Add function util_cauchy_param_estimate() Fix #130 - Add function tidy_t() - Also add plotting functions. Fix #151 - Add function tidy_mixture_density() Fix #150 - Add function util_geometric_stats_tbl() Fix #149 - Add function util_hypergeometric_stats_tbl() Fix #148 - Add function util_logistic_stats_tbl() Fix #147 - Add function util_lognormal_stats_tbl() Fix #146 - Add function util_negative_binomial_stats_tbl() Fix #145 - Add function util_normal_stats_tbl() Fix #144 - Add function util_pareto_stats_tbl() Fix #143 - Add function util_poisson_stats_tbl() Fix #142 - Add function util_uniform_stats_tbl() Fix #141 - Add function util_cauchy_stats_tbl() Fix #140 - Add function util_t_stats_tbl() Fix #139 - Add function util_f_stats_tbl() Fix #138 - Add function util_chisquare_stats_tbl() Fix #137 - Add function util_weibull_stats_tbl() Fix #136 - Add function util_gamma_stats_tbl() Fix #135 - Add function util_exponential_stats_tbl() Fix #134 - Add function util_binomial_stats_tbl() Fix #133 - Add function util_beta_stats_tbl()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-1-0","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.1.0","text":"Fix #110 - Bug fix, correct p calculation tidy_poisson() now produce correct probability chart auto plot functions. Fix #112 - Bug fix, correct p calculation tidy_hypergeometric() produce correct probability chart auto plot functions. Fix #115 - Fix spelling Quantile chart. Fix #117 - Fix probability plot x axis label. Fix #118 - Fix fill color combined auto plot Fix #122 - tidy_distribution_summary_tbl() function take output tidy_multi_single_dist() Fix #166 - Change plotting functions ggplot2::xlim(0, max_dy) ggplot2::ylim(0, max_dy) Fix #169 - Fix computation q column Fix #170 - Fix graphing quantile chart due #169","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-101","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.0.1","title":"TidyDensity 1.0.1","text":"CRAN release: 2022-03-27","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-0-1","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.0.1","text":"Fix #91 - Bug fix, change tidy_gamma() parameter .rate .scale Fixtidy_autoplot_functions incorporate change. Fixutil_gamma_param_estimate()sayscaleinstead ofrate` returned estimated parameters.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-0-1","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.0.1","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-1-0-1","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 1.0.1","text":"Fix #90 - Make sure .geom_smooth set TRUE ggplot2::xlim(0, max_dy) set. Fix #100 - tidy_multi_single_dist() failed distribution single parameter like tidy_poisson() Fix #96 - Enhance tidy_ distribution functions add attribute either discrete continuous helps autoplot process. Fix #97 - Enhance tidy_autoplot() use histogram lines density plot depending distribution discrete continuous. Fix #99 - Enhance tidy_multi_dist_autoplot() use histogram lines density plot depending distribution discrete continuous.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-100","dir":"Changelog","previous_headings":"","what":"TidyDensity 1.0.0","title":"TidyDensity 1.0.0","text":"CRAN release: 2022-03-08","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-1-0-0","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 1.0.0","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-1-0-0","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 1.0.0","text":"Fix #27 - Add function tidy_binomial() Fix #32 - Add function tidy_geometric() Fix #33 - Add function tidy_negative_binomial() Fix #34 - Add function tidy_zero_truncated_poisson() Fix #35 - Add function tidy_zero_truncated_geometric() Fix #36 - Add function tidy_zero_truncated_binomial() Fix #37 - Add function tidy_zero_truncated_negative_binomial() Fix #41 - Add function tidy_pareto1() Fix #42 - Add function tidy_pareto() Fix #43 - Add function tidy_inverse_pareto() Fix #58 - Add function tidy_random_walk() Fix #60 - Add function tidy_random_walk_autoplot() Fix #47 - Add function tidy_generalized_pareto() Fix #44 - Add function tidy_paralogistic() Fix #38 - Add function tidy_inverse_exponential() Fix #45 - Add function tidy_inverse_gamma() Fix #46 - Add function tidy_inverse_weibull() Fix #48 - Add function tidy_burr() Fix #49 - Add function tidy_inverse_burr() Fix #50 - Add function tidy_inverse_normal() Fix #51 - Add function tidy_generalized_beta() Fix #26 - Add function tidy_multi_single_dist() Fix #62 - Add function tidy_multi_dist_autoplot() Fix #66 - Add function tidy_combine_distributions() Fix #69 - Add functions tidy_kurtosis_vec(), tidy_skewness_vec(), tidy_range_statistic() Fix #75 - Add function util_beta_param_estimate() Fix #76 - Add function util_binomial_param_estimate() Fix #77 - Add function util_exponential_param_estimate() Fix #78 - Add function util_gamma_param_estimate() Fix #79 - Add function util_geometric_param_estimate() Fix #80 - Add function util_hypergeometric_param_estimate() Fix #81 - Add function util_lognormal_param_estimate() Fix #89 - Add function tidy_scale_zero_one_vec() Fix #87 - Add function tidy_combined_autoplot() Fix #82 - Add function util_logistic_param_estimate() Fix #83 - Add function util_negative_binomial_param_estimate() Fix #84 - Add function util_normal_param_estimate() Fix #85 - Add function util_pareto_param_estimate() Fix #86 - Add function util_poisson_param_estimate()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"fixes-and-minor-improvements-1-0-0","dir":"Changelog","previous_headings":"","what":"Fixes and Minor Improvements","title":"TidyDensity 1.0.0","text":"Fix #30 - Move crayon, rstudioapi, cli Suggests Imports due pillar longer importing. Fix #52 - Add parameter .geom_rug tidy_autoplot() function Fix #54 - Add parameter .geom_point tidy_autoplot() function Fix #53 - Add parameter .geom_smooth tidy_autoplot() function Fix #55 - Add parameter .geom_jitter tidy_autoplot() function Fix #57 - Fix tidy_autoplot() distribution tidy_empirical() legend argument fail. Fix #56 - Add attributes .n .num_sims (1L now) tidy_empirical() Fix #61 - Update _pkgdown.yml file update site. Fix #67 - Add param_grid, param_grid_txt, dist_with_params attributes tidy_ distribution functions. Fix #70 - Add ... grouping parameter tidy_distribution_summary_tbl() Fix #88 - Make column dist_type factor tidy_combine_distributions()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"tidydensity-001","dir":"Changelog","previous_headings":"","what":"TidyDensity 0.0.1","title":"TidyDensity 0.0.1","text":"CRAN release: 2022-01-21","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-0-0-1","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 0.0.1","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-0-0-1","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 0.0.1","text":"Fix #1 - Add function tidy_normal() Fix #4 - Add function tidy_gamma() Fix #5 - Add function tidy_beta() Fix #6 - Add function tidy_poisson() Fix #2 - Add function tidy_autoplot() Fix #11 - Add function tidy_distribution_summary_tbl() Fix #10 - Add function tidy_empirical() Fix #13 - Add function tidy_uniform() Fix #14 - Add function tidy_exponential() Fix #15 - Add function tidy_logistic() Fix #16 - Add function tidy_lognormal() Fix #17 - Add function tidy_weibull() Fix #18 - Add function tidy_chisquare() Fix #19 - Add function tidy_cauchy() Fix #20 - Add function tidy_hypergeometric() Fix #21 - Add function tidy_f()","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"minor-fixes-and-improvements-0-0-1","dir":"Changelog","previous_headings":"","what":"Minor Fixes and Improvements","title":"TidyDensity 0.0.1","text":"None","code":""},{"path":[]},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"breaking-changes-0-0-0-9000","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"TidyDensity 0.0.0.9000","text":"None","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"new-features-0-0-0-9000","dir":"Changelog","previous_headings":"","what":"New Features","title":"TidyDensity 0.0.0.9000","text":"Added NEWS.md file track changes package.","code":""},{"path":"https://www.spsanderson.com/TidyDensity/news/index.html","id":"fixes-and-minor-improvements-0-0-0-9000","dir":"Changelog","previous_headings":"","what":"Fixes and Minor Improvements","title":"TidyDensity 0.0.0.9000","text":"None","code":""}]