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DESCRIPTION
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DESCRIPTION
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Package: SpatPCA
Title: Regularized Principal Component Analysis for Spatial Data
Version: 1.3.7
Authors@R: c(person(
given = "Wen-Ting",
family = "Wang",
email = "egpivo@gmail.com",
role = c("aut", "cre"),
comment = c(ORCID = "0000-0003-3051-7302")
),
person(
given = "Hsin-Cheng",
family = "Huang",
email = "hchuang@stat.sinica.edu.tw",
role = "aut",
comment = c(ORCID = "0000-0002-5613-349X")
)
)
Description: Provide regularized principal component analysis incorporating smoothness, sparseness and orthogonality of eigen-functions
by using the alternating direction method of multipliers algorithm (Wang and Huang, 2017, <DOI:10.1080/10618600.2016.1157483>). The
method can be applied to either regularly or irregularly spaced data, including 1D, 2D, and 3D.
License: GPL (>= 2)
LazyData: true
ByteCompile: true
BugReports: https://github.com/egpivo/SpatPCA/issues
Depends:
R (>= 3.4.0)
Imports:
Rcpp (>= 1.0.12),
RcppParallel (>= 5.1.7),
ggplot2
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Suggests:
knitr,
rmarkdown,
testthat (>= 2.1.0),
dplyr (>= 1.0.3),
gifski,
tidyr,
fields,
scico,
plot3D,
pracma,
RColorBrewer,
maps,
covr,
styler,
V8
SystemRequirements: GNU make
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.2.3
Roxygen: list(markdown = TRUE)
URL: https://egpivo.github.io/SpatPCA/, https://github.com/egpivo/SpatPCA
Config/testthat/edition: 3