On Bayesian model and variable selection using MCMC

被引：259

作者：

Dellaportas, P

Forster, JJ

Ntzoufras, I

机构：

[1] Athens Univ Econ & Business, Dept Stat, Athens 10434, Greece

[2] Univ Southampton, Dept Math, Southampton SO17 1BJ, Hants, England

来源：

STATISTICS AND COMPUTING | 2002年 / 12卷 / 01期

关键词：

Gibbs sampler; independence sampler; Metropolis-Hastings; reversible jump;

D O I：

10.1023/A:1013164120801

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Several MCMC methods have been proposed for estimating probabilities of models and associated 'model-averaged' posterior distributions in the presence of model uncertainty. We discuss, compare, develop and illustrate several of these methods, focussing on connections between them.

引用

页码：27 / 36

页数：10

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