Ridge Selection Operator for Sparse Linear Regression // 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.