corrselect: Correlation-Based Variable Subset Selection

Provides functions to extract low-correlation variable subsets using exact graph-theoretic algorithms (e.g., Eppstein–Löffler–Strash, Bron–Kerbosch) as well as greedy and spectral heuristics. Supports both numeric and mixed-type data using generalized association measures.

Version: 2.0.1
Imports: Rcpp, methods, stats
LinkingTo: Rcpp
Suggests: GO.db, WGCNA, preprocessCore, impute, energy, minerva, knitr, rmarkdown
Published: 2025-09-08
DOI: 10.32614/CRAN.package.corrselect
Author: Gilles Colling [aut, cre]
Maintainer: Gilles Colling <gilles.colling051 at gmail.com>
BugReports: https://github.com/gcol33/corrselect/issues
License: MIT + file LICENSE
URL: https://gillescolling.com/corrselect/
NeedsCompilation: yes
Citation: corrselect citation info
Materials: README, NEWS
CRAN checks: corrselect results

Documentation:

Reference manual: corrselect.html , corrselect.pdf
Vignettes: Upcoming Features in corrselect 2.1.0 (source, R code)
Correlation Subset Selection with corrselect (source, R code)

Downloads:

Package source: corrselect_2.0.1.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): corrselect_2.0.1.tgz, r-oldrel (arm64): not available, r-release (x86_64): corrselect_2.0.1.tgz, r-oldrel (x86_64): corrselect_2.0.1.tgz

Linking:

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