Bounding convergence rates for Markov chains: An example of the use of computer algebra
被引:0
作者:
John E. Kolassa
论文数: 0引用数: 0
h-index: 0
机构:Rutgers University,
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).
机构:
Beijing Normal Univ, Sch Math Sci, Lab Math & Complex Syst, Minist Educ, Beijing 100875, Peoples R ChinaBeijing Normal Univ, Sch Math Sci, Lab Math & Complex Syst, Minist Educ, Beijing 100875, Peoples R China