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 SizeFormat
v93i03.pdfFulltext512.66 kBAdobe PDFView/Open
lmSubsets_0.5.tar.gzSupplement1.08 MBUnknownView/Open
v93i03-replication.zipSupplement422.65 kBUnknownView/Open
CORE Recommender
Show full item record

SCOPUSTM   
Citations

7
checked on Nov 6, 2023

WEB OF SCIENCETM
Citations

4
Last Week
0
Last month
0
checked on Oct 29, 2023

Page view(s)

366
Last Week
1
Last month
2
checked on Nov 21, 2024

Download(s)

1,122
checked on Nov 21, 2024

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons