Efficient Bayes factor estimation from the reversible jump output

被引:33
作者
Bartolucci, F [1 ]
Scaccia, L
Mira, A
机构
[1] Univ Perugia, Dept Econ Finance & Stat, I-06123 Perugia, Italy
[2] Univ Macerata, Dept Econ & Financial Inst, I-62100 Macerata, Italy
[3] Univ Insubria, Dept Econ, I-21100 Varese, Italy
关键词
Bayesian model choice; bridge sampling; marginal likelihood; Markov chain Monte Carlo; reversible jump;
D O I
10.1093/biomet/93.1.41
中图分类号
Q [生物科学];
学科分类号
07 [理学]; 0710 [生物学]; 09 [农学];
摘要
We propose a class of estimators of the Bayes factor which is based on an extension of the bridge sampling identity of Meng & Wong (1996) and makes use of the output of the reversible jump algorithm of Green (1995). Within this class we give the optimal estimator and also a suboptimal one which may be simply computed on the basis of the acceptance probabilities used within the reversible jump algorithm for jumping between models. The proposed estimators are very easily computed and lead to a substantial gain of efficiency in estimating the Bayes factor over the standard estimator based on the reversible jump output. This is illustrated through a series of Monte Carlo simulations involving a linear and a logistic regression model.
引用
收藏
页码:41 / 52
页数:12
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