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 |
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) |
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 |
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