期刊
ANNALS OF STATISTICS
卷 40, 期 3, 页码 1550-1577出版社
INST MATHEMATICAL STATISTICS-IMS
DOI: 10.1214/12-AOS1013
关键词
Model selection; variable selection; objective Bayes
资金
- Spanish Ministry of Education and Science [MTM2010-19528]
- NSF [DMS-06-35449, DMS-07-57549-001, DMS-10-07773]
- Division Of Mathematical Sciences
- Direct For Mathematical & Physical Scien [1007773] Funding Source: National Science Foundation
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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