msPCA: Sparse Principal Component Analysis with Multiple PrincipalComponents
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 [aut, cph], Jean Pauphilet [aut, cre, cph] |
| Maintainer: | Jean Pauphilet <jpauphilet at london.edu> |
| License: | MIT + fileLICENSE |
| 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:msPCA_0.1.0.zip, 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:
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