期刊
ANNALS OF STATISTICS
卷 39, 期 5, 页码 2740-2765出版社
INST MATHEMATICAL STATISTICS
DOI: 10.1214/11-AOS917
关键词
Bayes factor; model selection consistency; ridge regression; singular value decomposition; variable selection
资金
- Grants-in-Aid for Scientific Research [22300097, 23740067] Funding Source: KAKEN
For the normal linear model variable selection problem, we propose selection criteria based on a fully Bayes formulation with a generalization of Zellner's g-prior which allows for p > n. A special case of the prior formulation is seen to yield tractable closed forms for marginal densities and Bayes factors which reveal new model evaluation characteristics of potential interest.
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