doi:10.18637/jss.v094.i04>. This package allows users to perform the regression, classification, count regression and censored regression for (ultra) high dimensional data, and it also supports advanced usages like group variable selection and nuisance variable selection.">

bestridge: A Comprehensive R Package for Best Subset Selection (original) (raw)

The bestridge package is designed to provide a one-stand service for users to successfully carry out best ridge regression in various complex situations via the primal dual active set algorithm proposed by Wen, C., Zhang, A., Quan, S. and Wang, X. (2020) <doi:10.18637/jss.v094.i04>. This package allows users to perform the regression, classification, count regression and censored regression for (ultra) high dimensional data, and it also supports advanced usages like group variable selection and nuisance variable selection.

Version: 1.0.7
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 1.0.3), Matrix (≥ 1.2-6), MASS, pheatmap, survival
LinkingTo: Rcpp, RcppEigen
Suggests: knitr, rmarkdown
Published: 2021-10-10
DOI: 10.32614/CRAN.package.bestridge
Author: Liyuan Hu ORCID iD [aut, cre], Jin Zhu ORCID iD [aut], Junxian Zhu [aut], Kangkang Jiang [aut], Yanhang Zhang [aut], Xueqin Wang ORCID iD [aut], Canhong Wen [aut]
Maintainer: Liyuan Hu
License: GPL-3
NeedsCompilation: yes
Materials: NEWS
CRAN checks: bestridge results

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