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 ORCID iD [aut, cre], Hsin-Cheng Huang ORCID iD [aut]
Maintainer: Wen-Ting Wang <egpivo at>
License: GPL-3
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: NEWS
CRAN checks: SpatMCA results


Reference manual: SpatMCA.pdf


Package source: SpatMCA_1.0.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


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