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).

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>
License: GPL-2
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README
CRAN checks: SpatPCA results


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


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