Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/19427
Title: | lmSubsets: Exact Variable-Subset Selection in Linear Regression for R |
Authors: | Hofmann, Marc Gatu, Cristian Kontoghiorghes, Erricos John Colubi, Ana Zeileis, Achim |
Major Field of Science: | Natural Sciences |
Field Category: | Mathematics |
Keywords: | Best-subset regression;Linear regression;Model selection;R;Variable selection |
Issue Date: | Apr-2020 |
Source: | Journal of Statistical Software, 2020, vol. 93, no. 3 |
Volume: | 93 |
Issue: | 3 |
Journal: | Journal of Statistical Software |
Abstract: | 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 pre-determined 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. |
URI: | https://hdl.handle.net/20.500.14279/19427 |
ISSN: | 15487660 |
DOI: | 10.18637/jss.v093.i03 |
Rights: | Attribution-NonCommercial-NoDerivatives 4.0 International |
Type: | Article |
Affiliation : | University of Oviedo Cyprus University of Technology University of Iasi University of London Universität Innsbruck |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
v93i03.pdf | Fulltext | 512.66 kB | Adobe PDF | View/Open |
lmSubsets_0.5.tar.gz | Supplement | 1.08 MB | Unknown | View/Open |
v93i03-replication.zip | Supplement | 422.65 kB | Unknown | View/Open |
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