msPCA
0.5.0Sparse Principal Component Analysis with Multiple Principal Components
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Overview
About
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" (2026) doi:10.1287/opre.2023.0598. 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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13OK
Slowest check: 2.3 min · r-oldrel-windows-x86_64
Check history
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-04-2512 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-04-2212 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1811 OK · 2 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
Show 1 earlier snapshots
- NOTE2026-03-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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msPCA
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dimensionality-reductionprincipal-component-analysisr-packagesparse-pca
169 commits · Last activity 2026-06-29 · 0% stars, 30d
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Checks run against github.com/jeanpauphilet/mspca on 2026-07-19.
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5 external dependencies (excludes base and recommended)
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Package metadata
- First published
- 2025-12-09
- Total releases
- 6 / 1 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 12 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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