Fully Bayes factors with a generalized g-prior
Methodology
2012-02-24 v4 Statistics Theory
Statistics Theory
Abstract
For the normal linear model variable selection problem, we propose selection criteria based on a fully Bayes formulation with a generalization of Zellner's -prior which allows for . 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.
Cite
@article{arxiv.0801.4410,
title = {Fully Bayes factors with a generalized g-prior},
author = {Yuzo Maruyama and Edward I. George},
journal= {arXiv preprint arXiv:0801.4410},
year = {2012}
}
Comments
Published in at http://dx.doi.org/10.1214/11-AOS917 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)