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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: 0.1.0
Imports: Rcpp (≥ 1.0.11)
LinkingTo: Rcpp, RcppEigen
Published: 2025-12-09
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_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: msPCA_0.1.0.zip
macOS binaries: r-release (arm64): msPCA_0.1.0.tgz, r-oldrel (arm64): msPCA_0.1.0.tgz, r-release (x86_64): msPCA_0.1.0.tgz, r-oldrel (x86_64): msPCA_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=msPCA to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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