Date of this Version
The Annals of Statistics
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.
Bayes factor, model selection consistency, ridge regression, singular value decomposition, variable selection
Maruyama, Y., & George, E. I. (2011). Fully Bayes Factors With a Generalized g-Prior. The Annals of Statistics, 39 (5), 2740-2765. http://dx.doi.org/10.1214/11-AOS917
Date Posted: 27 November 2017
This document has been peer reviewed.