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Study project of Statistical Rethinking, 2nd edition, Richard McElreath

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rethinking2020

Lifecycle: stable R 4.2.1

rethinking2020 is a study project of Statistical Rethinking, second edition, by Richard McElreath. [@elreath2020]

Aknowledgement

Many thanks to Richard McElreath who wrote Statistical Rethinking to make Bayesian statistics so interesting.

This study project is inspired by Solomon Kurtz who did wonderful work. It can be found at Solomon Kurtz.

Packages

The packages used in this project are as follows.

Modelizations and data processing

Package Comment
rethinking This R package accompanies a course and book on Bayesian data analysis: McElreath 2020. Statistical Rethinking, 2nd edition.
brms Used to do pretty much all models and computations.
loo Used by both rethinking and brms to compute WAIC and LOO. See section 7.5 in chapter for more details.
posterior Used to work with the output of Bayesian models.
tidybayes Bayesian statistics do require a lot of data processing. tidybayes is incredibly helpful in providing a constant and efficient way of coding the data processing.
bayestestR A comprehensive and consistent set of functions to analyze and describe posterior distributions.
tidyverse The package for data science in general.
extraDistr has many extra distributions such as BetaBinom, NegBetaBinom, HalfCauchy, ZIP, Pareto, etc. which are useful in real-world applications and usually dispersed among many different packages.
ggmcmc tool for assessing and diagnosing convergence of Markov Chain Monte Carlo simulations, as well as for graphically display results from full MCMC analysis
simpr tidyverse-friendly framework for generating simulated data, fitting models on simulations, and tidying model results.
modelr functions that help you create elegant pipelines when modelling
gtools functions to assist in R programming, including
logit and inv.logit functions used in many places in this project

Visualizations

Package Comment
ggdist tidybayes relies heavily on the ggdist and reexport very many of it's functions. In addition ggdist is useful for both a frequencist as well as a bayesian approach.
bayesplot Used as complement when ggdist and tidybayes do not provide a satisfactory solution.
ggplot2 Vizualisations using the grammar of graphics.
scales Provide the internal scaling infrastructure used by ggplot2
paletteer A nice package to manage color and shape palettes.

Graphs

Package Comment
dagitty Draw and analyse causal diagrams
ggdag R package to visualize and analyze causal directed acyclic graphs
tidygraph To manipulate graph data
ggraph To visualize graphs

Miscellaneous

Package Comment
xfun The function xfun::cache_rds is used for caching which is used several times in almost every chapter.

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Study project of Statistical Rethinking, 2nd edition, Richard McElreath

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