Efficient estimate of Bayes factors from Reversible Jump output

Francesco Bartolucci and Mira Antonietta ()
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Mira Antonietta: Department of Economics, University of Insubria, Italy

Economics and Quantitative Methods from Department of Economics, University of Insubria

Abstract: We exend Meng and Wong (1996) identity from a fixed to a varying dimentional setting. The identity is a very powerful tool to estimate ratios of normalizing constants and thus can be used to evaluate Bayes factors. The extention is driven by the reversibler jump algorithm so that the output from the semplar can be directly used to efficiently estimate the required Bayes factor. Two applications, involving linear and logistic regression models, illustrate the advantages of the suggested approach with respect to alternatives previously proposed in the literature.

Keywords: Bayes factor; Bayesian modeel choice; Marginal likelihood; Markov chain Monte Carlo; Reversible jump (search for similar items in EconPapers)
Pages: 16 pages
Date: 2003-10
New Economics Papers: this item is included in nep-ecm and nep-rmg
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Persistent link: https://EconPapers.repec.org/RePEc:ins:quaeco:qf0314

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