General methods for monitoring convergence of iterative simulations

被引:4992
作者
Brooks, SP
Gelman, A
机构
[1] Univ Bristol, Dept Math, Bristol BS8 1TW, Avon, England
[2] Columbia Univ, Dept Stat, New York, NY 10027 USA
关键词
convergence diagnosis; inference; Markov chain Monte Carlo;
D O I
10.2307/1390675
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 generalize the method proposed by Gelman and Rubin (1992a) for monitoring the convergence of iterative simulations by comparing between and within variances of multiple chains, in order to obtain a family of tests for convergence. We review methods of inference from simulations in older to develop convergence-monitoring summaries that are relevant for the purposes for which the simulations are used. We recommend applying a battery of tests for mixing based on the comparison of inferences from individual sequences and from the mixture of sequences. Finally, we discuss multivariate analogues, for assessing convergence of several parameters simultaneously.
引用
收藏
页码:434 / 455
页数:22
相关论文
共 24 条
[1]  
[Anonymous], 1979, Multivariate analysis
[2]  
APPLEGATE D, 1990, 500 CARN U
[3]  
Asmussen S., 1992, ACM Transactions on Modeling and Computer Simulation, V2, P130, DOI 10.1145/137926.137932
[4]  
BROOKS SP, IN PRESS STAT COMPUT
[5]  
Carlin B. P., 2001, BAYES EMPIRICAL BAYE
[6]   Markov chain Monte Carlo convergence diagnostics: A comparative review [J].
Cowles, MK ;
Carlin, BP .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1996, 91 (434) :883-904
[7]   BAYESIAN-INFERENCE FOR GENERALIZED LINEAR AND PROPORTIONAL HAZARDS MODELS VIA GIBBS SAMPLING [J].
DELLAPORTAS, P ;
SMITH, AFM .
APPLIED STATISTICS-JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C, 1993, 42 (03) :443-459
[8]  
Efron B., 1994, INTRO BOOTSTRAP, V57, DOI DOI 10.1201/9780429246593
[9]  
Fisher Ronald A., 1935, DESIGN EXPT
[10]   EFFICIENT PARAMETRIZATIONS FOR NORMAL LINEAR MIXED MODELS [J].
GELFAND, AE ;
SAHU, SK ;
CARLIN, BP .
BIOMETRIKA, 1995, 82 (03) :479-488