Year: 2026
Type: dataset
Abstract: 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.
Authors: Murat Genc, Adewale Lukman
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W7167465474