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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | RSO_1.0.0.tar.gz |
111.3 KiB |
1.0.0 |
rolling linux/noble R-4.5 | RSO_1.0.0.tar.gz |
113.2 KiB |
1.0.0 |
rolling source/ R- | RSO_1.0.0.tar.gz |
9.2 KiB |
1.0.0 |
latest linux/jammy R-4.5 | RSO_1.0.0.tar.gz |
111.3 KiB |
1.0.0 |
latest linux/noble R-4.5 | RSO_1.0.0.tar.gz |
113.2 KiB |
1.0.0 |
latest source/ R- | RSO_1.0.0.tar.gz |
9.2 KiB |
1.0.0 |
2026-04-23 source/ R- | RSO_1.0.0.tar.gz |
0 B |