TY - JOUR AU - Hofmann, Marc AU - Gatu, Cristian AU - Kontoghiorghes, Erricos J. AU - Colubi, Ana AU - Zeileis, Achim PY - 2020/04/28 Y2 - 2024/03/29 TI - lmSubsets: Exact Variable-Subset Selection in Linear Regression for R JF - Journal of Statistical Software JA - J. Stat. Soft. VL - 93 IS - 3 SE - Articles DO - 10.18637/jss.v093.i03 UR - https://www.jstatsoft.org/index.php/jss/article/view/v093i03 SP - 1 - 21 AB - An R package for computing the all-subsets regression problem is presented. The proposed algorithms are based on computational strategies recently developed. A novel algorithm for the best-subset regression problem selects subset models based on a predetermined criterion. The package user can choose from exact and from approximation algorithms. The core of the package is written in C++ and provides an efficient implementation of all the underlying numerical computations. A case study and benchmark results illustrate the usage and the computational efficiency of the package. ER -