Journal
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
Volume 103, Issue 481, Pages 410-423Publisher
AMER STATISTICAL ASSOC
DOI: 10.1198/016214507000001337
Keywords
AIC; Bayesian model averaging; BIC; cauchy; empirical Bayes; Gaussian hypergeometric functions; model selection; Zellner-Siow priors
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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.
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