Markov-chain Monte Carlo: Some practical implications of theoretical results

被引：71
|
作者：
Roberts, GO
Rosenthal, JS
机构：
[1] Univ Cambridge, Stat Lab, Cambridge CB2 1SB, England
[2] Univ Toronto, Dept Stat, Toronto, ON M5S 3G3, Canada
来源：
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE | 1998年 / 26卷 / 01期
关键词：
Markov chain; Monte Carlo; MCMC; Gibbs sampler; Metropolis-Hastings algorithm;
D O I：
10.2307/3315667
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
We review and discuss some recent progress in the theory of Markov-chain Monte Carlo applications, particularly oriented to applications in statistics. We attempt to assess the relevance of this theory for practical applications.
引用
收藏
页码：5 / 20
页数：16
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