DESCRIPTION

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