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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.

Versions across snapshots

VersionRepositoryFileSize
0.2.0 rolling linux/jammy R-4.5 msPCA_0.2.0.tar.gz 107.9 KiB
0.2.0 rolling linux/noble R-4.5 msPCA_0.2.0.tar.gz 112.6 KiB
0.2.0 rolling source/ R- msPCA_0.2.0.tar.gz 12.4 KiB
0.2.0 latest linux/jammy R-4.5 msPCA_0.2.0.tar.gz 107.9 KiB
0.2.0 latest linux/noble R-4.5 msPCA_0.2.0.tar.gz 112.6 KiB
0.2.0 latest source/ R- msPCA_0.2.0.tar.gz 12.4 KiB
0.2.0 2026-04-26 source/ R- msPCA_0.2.0.tar.gz 12.4 KiB
0.2.0 2026-04-23 source/ R- msPCA_0.2.0.tar.gz 12.4 KiB
0.2.0 2026-04-09 windows/windows R-4.5 msPCA_0.2.0.zip 430.0 KiB

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