SpatPCA: Regularized Principal Component Analysis for Spatial Data

Provide regularized principal component analysis incorporating smoothness, sparseness and orthogonality of eigenfunctions by using the alternating direction method of multipliers algorithm. The method can be applied to either regularly or irregularly spaced data (Wang and Huang, 2017).

Version: 1.1.1.2
Imports: Rcpp, RcppParallel (≥ 0.11.2)
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Published: 2017-03-18
Author: Wen-Ting Wang, Hsin-Cheng Huang
Maintainer: Wen-Ting Wang <egpivo at gmail.com>
BugReports: https://github.com/egpivo/SpatPCA/issues
License: GPL-2
URL: https://github.com/egpivo/SpatPCA
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README
CRAN checks: SpatPCA results

Downloads:

Reference manual: SpatPCA.pdf
Package source: SpatPCA_1.1.1.2.tar.gz
Windows binaries: r-devel: SpatPCA_1.1.1.2.zip, r-release: SpatPCA_1.1.1.2.zip, r-oldrel: SpatPCA_1.1.1.2.zip
OS X Mavericks binaries: r-release: SpatPCA_1.1.1.2.tgz, r-oldrel: SpatPCA_1.1.1.2.tgz
Old sources: SpatPCA archive

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