HCmodelSets: An R package for specifying sets of well-fitting models in high dimensions
File(s)
Published version
Author(s)
Hoeltgebaum, Henrique
Battey, Heather
Type
Journal Article
Abstract
In the context of regression with a large number of explanatory variables, Cox and Battey(2017) emphasize that if there are alternative reasonable explanations of the data that are statisticallyindistinguishable, one should aim to specify as many of these explanations as is feasible. The standardpractice, by contrast, is to report a single model effective for prediction. The present paper illustratesthe R implementation of the new ideas in the packageHCmodelSets, using simple reproducibleexamples and real data. Results of some simulation experiments are also reported.
Date Issued
2020-01-06
Date Acceptance
2019-12-25
Citation
The R Journal, 2020, 11 (2), pp.370-379
ISSN
2073-4859
Publisher
The R Foundation for Statistical Computing
Start Page
370
End Page
379
Journal / Book Title
The R Journal
Volume
11
Issue
2
Copyright Statement
This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/)
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (EPSRC)
Grant Number
EP/P002757/1
EP/P002757/1
Subjects
0104 Statistics
0803 Computer Software
Publication Status
Published