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Fully Bayes factors with a generalized \(g\)-prior. (English) Zbl 1231.62036

Summary: For the normal linear model variable selection problem, we propose selection criteria based on a fully Bayes formulation with a generalization of A. Zellner’s \(g\)-prior [Stud. Bayesian Econ. Stat. 6, 233–243 (1986; Zbl 0655.62071)] 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.

MSC:

62F15 Bayesian inference
62J05 Linear regression; mixed models
62J07 Ridge regression; shrinkage estimators (Lasso)
62H12 Estimation in multivariate analysis
62C10 Bayesian problems; characterization of Bayes procedures
65C60 Computational problems in statistics (MSC2010)

Citations:

Zbl 0655.62071
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References:

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