Open Access
June 2012 Criteria for Bayesian model choice with application to variable selection
M. J. Bayarri, J. O. Berger, A. Forte, G. García-Donato
Ann. Statist. 40(3): 1550-1577 (June 2012). DOI: 10.1214/12-AOS1013


In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to propose differing prior choices. We first formalize the most general and compelling of the various criteria that have been suggested, together with a new criterion. We then illustrate the potential of these criteria in determining objective model selection priors by considering their application to the problem of variable selection in normal linear models. This results in a new model selection objective prior with a number of compelling properties.


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M. J. Bayarri. J. O. Berger. A. Forte. G. García-Donato. "Criteria for Bayesian model choice with application to variable selection." Ann. Statist. 40 (3) 1550 - 1577, June 2012.


Published: June 2012
First available in Project Euclid: 5 September 2012

zbMATH: 1257.62023
MathSciNet: MR3015035
Digital Object Identifier: 10.1214/12-AOS1013

Primary: 62J05 , 62J15
Secondary: 62C10

Keywords: Model selection , objective Bayes , Variable selection

Rights: Copyright © 2012 Institute of Mathematical Statistics

Vol.40 • No. 3 • June 2012
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