GEOMETRIC ERGODICITY AND HYBRID MARKOV CHAINS

被引：185
|
作者：
Roberts, Gareth O. [1 ]
Rosenthal, Jeffrey S. [2 ]
机构：
[1] Univ Cambridge, Stat Lab, Cambridge CB2 1SB, England
[2] Univ Toronto, Dept Stat, Toronto, ON M5S 3G3, Canada
来源：
ELECTRONIC COMMUNICATIONS IN PROBABILITY | 1997年 / 2卷
关键词：
Ergodicity; Markov Chain; Monte Carlo;
D O I：
10.1214/ECP.v2-981
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：
Various notions of geometric ergodicity for Markov chains on general state spaces exist. In this paper, we review certain relations and implications among them. We then apply these results to a collection of chains commonly used in Markov chain Monte Carlo simulation algorithms, the so-called hybrid chains. We prove that under certain conditions, a hybrid chain will "inherit" the geometric ergodicity of its constituent parts.
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页码：13 / 25
页数：13
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