Implements the Ridge Selection Operator (RSO) for variable selection in linear regression as proposed by Wu (2021) <doi:10.1080/00401706.2020.1791254>. The RSO method extends classical ridge regression by using individually penalized ridge parameters, inducing sparsity through reciprocal penalty parameters. This package provides a fast C++ implementation ('RSOFast') using 'Armadillo' linear algebra routines. The fast implementation precomputes matrix products, uses Cholesky factorization with primal/dual switching, and performs golden-section search for coordinate optimization.
| Version: | 1.0.0 |
| Imports: | Rcpp |
| LinkingTo: | Rcpp, RcppArmadillo |
| Published: | 2026-07-06 |
| DOI: | 10.32614/CRAN.package.RSO |
| Author: | Murat Genc [aut, cre], Adewale Lukman [aut] |
| Maintainer: | Murat Genc <mgenc at cu.edu.tr> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| CRAN checks: | RSO results |
| Reference manual: | RSO.html , RSO.pdf |
| Package source: | RSO_1.0.0.tar.gz |
| Windows binaries: | r-devel: RSO_1.0.0.zip, r-release: RSO_1.0.0.zip, r-oldrel: RSO_1.0.0.zip |
| macOS binaries: | r-release (arm64): RSO_1.0.0.tgz, r-oldrel (arm64): RSO_1.0.0.tgz, r-release (x86_64): RSO_1.0.0.tgz, r-oldrel (x86_64): RSO_1.0.0.tgz |
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