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CRAN: Package msPCA

msPCA: Sparse Principal Component Analysis with Multiple Principal Components

Implements an algorithm for computing multiple sparse principal components of a dataset. The method is based on Cory-Wright and Pauphilet "Sparse PCA with Multiple Principal Components" (2022) <doi:10.48550/arXiv.2209.14790>. The algorithm uses an iterative deflation heuristic with a truncated power method applied at each iteration to compute sparse principal components with controlled sparsity.

Version: 0.2.0
Imports: Rcpp (≥ 1.0.11)
LinkingTo: Rcpp, RcppEigen
Published: 2026-01-12
DOI: 10.32614/CRAN.package.msPCA
Author: Ryan Cory-Wright ORCID iD [aut, cph], Jean Pauphilet ORCID iD [aut, cre, cph]
Maintainer: Jean Pauphilet <jpauphilet at london.edu>
License: MIT + file LICENSE
NeedsCompilation: yes
Materials: README, NEWS
CRAN checks: msPCA results

Documentation:

Reference manual: msPCA.html , msPCA.pdf

Downloads:

Package source: msPCA_0.2.0.tar.gz
Windows binaries: r-devel: msPCA_0.2.0.zip, r-release: msPCA_0.2.0.zip, r-oldrel: msPCA_0.2.0.zip
macOS binaries: r-release (arm64): msPCA_0.2.0.tgz, r-oldrel (arm64): msPCA_0.2.0.tgz, r-release (x86_64): msPCA_0.2.0.tgz, r-oldrel (x86_64): msPCA_0.2.0.tgz
Old sources: msPCA archive

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