gBF: A Fully Bayes Factor with a Generalized g-prior

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 characteristics of potential interest. AMS 2000 subject classifications: Primary 62F07, 62F15; secondary 62C10.

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