collinear: Automated Multicollinearity Management
Effortless multicollinearity management in data frames with both numeric and categorical variables for statistical and machine learning applications. The package simplifies multicollinearity analysis by combining four robust methods: 1) target encoding for categorical variables (Micci-Barreca, D. 2001 <doi:10.1145/507533.507538>); 2) automated feature prioritization to prevent key variable loss during filtering; 3) pairwise correlation for all variable combinations (numeric-numeric, numeric-categorical, categorical-categorical); and 4) fast computation of variance inflation factors.
| Version: | 2.0.0 |
| Depends: | R (≥ 4.0) |
| Imports: | progressr, future.apply, mgcv, rpart, ranger |
| Suggests: | future, testthat (≥ 3.0.0), spelling |
| Published: | 2024-11-08 |
| DOI: | 10.32614/CRAN.package.collinear |
| Author: | Blas M. Benito 
[aut, cre, cph] |
| Maintainer: | Blas M. Benito <blasbenito at gmail.com> |
| BugReports: | https://github.com/blasbenito/collinear/issues |
| License: | MIT + file LICENSE |
| URL: | https://blasbenito.github.io/collinear/ |
| NeedsCompilation: | no |
| Language: | en-US |
| Citation: | collinear citation info |
| Materials: | README NEWS |
| CRAN checks: | collinear results |
Documentation:
| Reference manual: | collinear.pdf |
Downloads:
| Package source: | collinear_2.0.0.tar.gz |
| Windows binaries: | r-devel: collinear_1.1.1.zip, r-release: collinear_2.0.0.zip, r-oldrel: collinear_2.0.0.zip |
| macOS binaries: | r-release (arm64): collinear_2.0.0.tgz, r-oldrel (arm64): collinear_2.0.0.tgz, r-release (x86_64): collinear_2.0.0.tgz, r-oldrel (x86_64): collinear_2.0.0.tgz |
| Old sources: | collinear archive |
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