Methods and Tools for Bayesian Variable Selection and Model Averaging in Normal Linear Regression. (13th February 2018)

• Record Type: Journal Article
• Authors: Forte, Anabel; Garcia‐Donato, Gonzalo; Steel, Mark
• Is Part Of: International statistical review. Volume 86:Number 2(2018)
• Page Start: 237
• Page End: 258
• Publication Date: 2018-02-13
• Subjects: Statistics -- Periodicals; Statistics -- Bibliography -- Periodicals; Statistics -- Bibliography; Statistics -- Periodicals; Statistique; Statistique -- Périodiques; Statistique -- Bibliographie -- Périodiques; Statistique -- Étude et enseignement -- Périodiques; Statistique -- Étude et enseignement -- Bibliographie -- Périodiques; Ressource Internet (Descripteur de forme); Périodique électronique (Descripteur de forme); 519.2
• DOI: 10.1111/insr.12249
• Languages: English
• ISSNs: 0306-7734

Abstract

Summary: 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.