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msPCA

Sparse Principal Component Analysis with Multiple Principal Components

v0.2.0 · Jan 12, 2026 · MIT + file LICENSE

Description

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.

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r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
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r-oldrel-windows-x86_64 OK
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r-release-windows-x86_64 OK
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OK r-devel-linux-x86_64-debian-gcc

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OK r-devel-linux-x86_64-fedora-clang

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OK r-devel-linux-x86_64-fedora-gcc

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OK r-devel-macos-arm64

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OK r-devel-windows-x86_64

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NOTE r-oldrel-macos-arm64

installed package size

  installed size is 12.7Mb
  sub-directories of 1Mb or more:
    libs  12.6Mb
NOTE r-oldrel-macos-x86_64

installed package size

  installed size is 12.9Mb
  sub-directories of 1Mb or more:
    libs  12.8Mb
OK r-oldrel-windows-x86_64

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OK r-patched-linux-x86_64

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OK r-release-linux-x86_64

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Check History

NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-oldrel-macos-arm64

installed package size

  installed size is 12.7Mb
  sub-directories of 1Mb or more:
    libs  12.6Mb
NOTE r-oldrel-macos-x86_64

installed package size

  installed size is 12.9Mb
  sub-directories of 1Mb or more:
    libs  12.8Mb

Dependency Network

Dependencies Reverse dependencies Rcpp msPCA

Version History

new 0.2.0 Mar 9, 2026