Package: RSO 1.0.0

Murat Genc

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.

Authors:Murat Genc [aut, cre], Adewale Lukman [aut]

RSO_1.0.0.tar.gz
RSO_1.0.0.zip(r-4.7-x86_64)RSO_1.0.0.zip(r-4.7-arm64)RSO_1.0.0.zip(r-4.6-x86_64)RSO_1.0.0.zip(r-4.6-arm64)
RSO_1.0.0.tar.gz(r-4.7-arm64)RSO_1.0.0.tar.gz(r-4.7-x86_64)RSO_1.0.0.tar.gz(r-4.6-arm64)RSO_1.0.0.tar.gz(r-4.6-x86_64)
RSO_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
RSO/json (API)

# Install 'RSO' in R:
install.packages('RSO', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascppopenmp

1.00 score 188 downloads 4 exports 2 dependencies

Last updated from:9de59d1f42. Checks:10 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK101
linux-devel-x86_64OK112
source / vignettesOK192
linux-release-arm64OK99
linux-release-x86_64OK113
windows-devel-arm64OK226
windows-devel-x86_64OK147
windows-release-arm64OK329
windows-release-x86_64OK112
wasm-releaseOK99

Exports:ridgeregridgereg_dfridgeRegPrecompRSOFast

Dependencies:RcppRcppArmadillo