BeSS: An R Package for Best Subset Selection in Linear, Logistic and CoxPH Models
Computation
2020-03-10 v2
Abstract
We introduce a new R package, BeSS, for solving the best subset selection problem in linear, logistic and Cox's proportional hazard (CoxPH) models. It utilizes a highly efficient active set algorithm based on primal and dual variables, and supports sequential and golden search strategies for best subset selection. We provide a C++ implementation of the algorithm using Rcpp interface. We demonstrate through numerical experiments based on enormous simulation and real datasets that the new BeSS package has competitive performance compared to other R packages for best subset selection purpose.
Cite
@article{arxiv.1709.06254,
title = {BeSS: An R Package for Best Subset Selection in Linear, Logistic and CoxPH Models},
author = {Canhong Wen and Aijun Zhang and Shijie Quan and Xueqin Wang},
journal= {arXiv preprint arXiv:1709.06254},
year = {2020}
}
Comments
To appear in Journal of Statistical Software