Package: SpatPCA
Title: Regularized Principal Component Analysis for Spatial Data
Version: 1.3.5
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-3
ByteCompile: true
BugReports: https://github.com/egpivo/SpatPCA/issues
Depends: R (>= 3.4.0)
Imports: Rcpp (>= 1.0.10), 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
URL: https://github.com/egpivo/SpatPCA
Config/testthat/edition: 3
NeedsCompilation: yes
Packaged: 2023-11-12 12:12:19 UTC; joseph
Author: Wen-Ting Wang [aut, cre] (<https://orcid.org/0000-0003-3051-7302>),
  Hsin-Cheng Huang [aut] (<https://orcid.org/0000-0002-5613-349X>)
Maintainer: Wen-Ting Wang <egpivo@gmail.com>
Repository: CRAN
Date/Publication: 2023-11-13 09:33:19 UTC
Built: R 4.2.3; x86_64-w64-mingw32; 2024-04-24 01:58:59 UTC; windows
ExperimentalWindowsRuntime: ucrt
Archs: x64
