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 |
| Maintainer: | Jean Pauphilet <jpauphilet at london.edu> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | yes |
| Materials: | README, NEWS |
| CRAN checks: | msPCA results |
| Reference manual: | msPCA.html , msPCA.pdf |
| 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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