Forte, Anabel, Garcia-Donato, Gonzalo and Steel, Mark F. J. (2018) Methods and tools for Bayesian variable selection and model averaging in normal linear regression. International Statistical Review, 86 (2). pp. 237-258. doi:10.1111/insr.12249

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Abstract

In this paper, we briefly review the main methodological aspects concerned with the application of the Bayesian approach to model choice and model averaging in the context of variable selection in regression models. This includes prior elicitation, summaries of the posterior distribution and computational strategies. We then examine and compare various publicly available R-packages, summarizing and explaining the differences between packages and giving recommendations for applied users. We find that all packages reviewed (can) lead to very similar results, but there are potentially important differences in flexibility and efficiency of the packages.

Item Type:	Journal Article
Divisions:	Faculty of Science > Statistics
Journal or Publication Title:	International Statistical Review
Publisher:	Wiley-Blackwell Publishing Ltd.
ISSN:	0306-7734
Official Date:	August 2018
Dates:	Date Event August 2018 Published 13 February 2018 Available 12 December 2017 Accepted
Volume:	86
Number:	2
Page Range:	pp. 237-258
DOI:	10.1111/insr.12249
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access

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