SpatMCA: Regularized Spatial Maximum Covariance Analysis

Provide regularized maximum covariance analysis incorporating smoothness, sparseness and orthogonality of couple patterns by using the alternating direction method of multipliers algorithm. The method can be applied to either regularly or irregularly spaced data, including 1D, 2D, and 3D (Wang and Huang, 2017 <doi:10.1002/env.2481>).

Version:	1.0.4
Depends:	R (≥ 3.4.0)
Imports:	Rcpp, RcppParallel (≥ 0.11.2), MASS, ggplot2, scales
LinkingTo:	Rcpp, RcppArmadillo, RcppParallel
Suggests:	testthat (≥ 2.1.0), RColorBrewer, plot3D, pracma, spTimer, fields, maps, covr, V8
Published:	2023-11-21
DOI:	10.32614/CRAN.package.SpatMCA
Author:	Wen-Ting Wang [aut, cre], Hsin-Cheng Huang [aut]
Maintainer:	Wen-Ting Wang <egpivo at gmail.com>
BugReports:	https://github.com/egpivo/SpatMCA/issues
License:	GPL-3
URL:	https://github.com/egpivo/SpatMCA
NeedsCompilation:	yes
SystemRequirements:	GNU make
Materials:	NEWS
CRAN checks:	SpatMCA results

Documentation:

Reference manual:

SpatMCA.pdf

Downloads:

Package source:	SpatMCA_1.0.4.tar.gz
Windows binaries:	r-devel: SpatMCA_1.0.4.zip, r-release: SpatMCA_1.0.4.zip, r-oldrel: SpatMCA_1.0.4.zip
macOS binaries:	r-release (arm64): SpatMCA_1.0.4.tgz, r-oldrel (arm64): SpatMCA_1.0.4.tgz, r-release (x86_64): SpatMCA_1.0.4.tgz, r-oldrel (x86_64): SpatMCA_1.0.4.tgz
Old sources:	SpatMCA archive

Linking:

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