Bounding convergence rates for Markov chains: An example of the use of computer algebra

被引：0
|
作者：
John E. Kolassa
机构：
[1] Rutgers University,
来源：
Statistics and Computing | 2001年 / 11卷
关键词：
Markov chain; Monte Carlo; computer algebra;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Kolassa and Tanner (J. Am. Stat. Assoc. (1994) 89, 697–702) present the Gibbs-Skovgaard algorithm for approximate conditional inference. Kolassa (Ann Statist. (1999), 27, 129–142) gives conditions under which their Markov chain is known to converge. This paper calculates explicity bounds on convergence rates in terms calculable directly from chain transition operators. These results are useful in cases like those considered by Kolassa (1999).
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页码：83 / 87
页数：4
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