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 contribution||Mixtures of g priors for Bayesian variable selection|
|Pages (from-to)||410 - 423|
|Number of pages||14|
|Journal||Journal of the American Statistical Association|
|Publication status||Published - Mar 2008|