Posterior Odds with a Generalized Hyper- g -Prior

Edward I. George and Yuzo Maruyama

Econometric Reviews, 2014, vol. 33, issue 1-4, 251-269

Abstract: Averaged orthogonal rotations of Zellner's g-prior yield general, interpretable, closed form Bayes factors for the normal linear model variable selection problem. Coupled with a model space prior that balances the weight between the identifiable and the unidentifiable models, limiting forms for the posterior odds ratios are seen to yield new expressions for high dimensional model choice.

Date: 2014
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Citations: View citations in EconPapers (4)

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DOI: 10.1080/07474938.2013.807181

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