RSO: 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.
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