Mixtures of g priors for Bayesian variable selection

F Liang, RMB Paulo, G Molina, M Clyde, J Berger

Research output: Contribution to journalArticle (Academic Journal)peer-review

543 Citations (Scopus)

Abstract

Zellner's g prior remains a popular conventional prior for use in Bayesian variable selection, despite several undesirable consistency issues. In this article we study mixtures of g priors as an alternative to default g priors that resolve many of the problems with the original formulation while maintaining the computational tractability that has made the g prior so popular. We present theoretical properties of the mixture g priors and provide real and simulated examples to compare the mixture formulation with fixed g priors, empirical Bayes approaches, and other default procedures.
Translated title of the contributionMixtures of g priors for Bayesian variable selection
Original languageEnglish
Pages (from-to)410 - 423
Number of pages14
JournalJournal of the American Statistical Association
Volume103 (481)
DOIs
Publication statusPublished - Mar 2008

Bibliographical note

Publisher: American Statistical Association

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