Mixtures of g-priors for Bayesian variable selection

Mixtures of g-priors for Bayesian variable selection (2008)

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by Feng Liang , Rui Paulo , German Molina , Merlise A. Clyde , Jim O. Berger

Venue:	Journal of the American Statistical Association
Citations:	14 - 4 self

BibTeX

@ARTICLE{Liang08mixturesof,
    author = {Feng Liang and Rui Paulo and German Molina and Merlise A. Clyde and Jim O. Berger},
    title = {Mixtures of g-priors for Bayesian variable selection},
    journal = {Journal of the American Statistical Association},
    year = {2008},
    pages = {423}
}

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Abstract

Zellner’s g-prior remains a popular conventional prior for use in Bayesian variable selection, despite several undesirable consistency issues. In this paper, 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.

Citations

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