Annals of Statistics

Fully Bayes factors with a generalized g-prior

Yuzo Maruyama and Edward I. George

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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.

Article information

Ann. Statist., Volume 39, Number 5 (2011), 2740-2765.

First available in Project Euclid: 22 December 2011

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Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Primary: 62F07: Ranking and selection 62F15: Bayesian inference
Secondary: 62C10: Bayesian problems; characterization of Bayes procedures

Bayes factor model selection consistency ridge regression singular value decomposition variable selection


Maruyama, Yuzo; George, Edward I. Fully Bayes factors with a generalized g -prior. Ann. Statist. 39 (2011), no. 5, 2740--2765. doi:10.1214/11-AOS917.

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