lmSubsets: Exact Variable-Subset Selection in Linear Regression for R
Dublin Core
Title
lmSubsets: Exact Variable-Subset Selection in Linear Regression for R
Subject
linear regression, model selection, variable selection, best-subset regression, R
Description
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.
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.
Creator
Marc Hofmann
Source
https://www.jstatsoft.org/article/view/v093i03
Publisher
University of Oviedo
Cyprus University of Technology
Cyprus University of Technology
Date
April 2020
Contributor
Fajar bagus W
Format
PDF
Language
Inggris
Type
Text
Files
Collection
Citation
Marc Hofmann, “lmSubsets: Exact Variable-Subset Selection in Linear Regression for R,” Repository Horizon University Indonesia, accessed April 4, 2025, https://repository.horizon.ac.id/items/show/8122.