Ridge Selection Operator for Sparse Linear Regression R package RSO version 1.0.0 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. Software Imports: Rcpp LinkingTo: Rcpp, RcppArmadillo Murat Genc <mgenc@cu.edu.tr> Comprehensive R Archive Network (CRAN) Murat Genc [aut, cre], Adewale Lukman [aut] GPL (>= 3) 2026-07-06 application/tgz https://CRAN.R-project.org/package=RSO doi:10.32614/CRAN.package.RSO