Sensitivity and convergence of uniformly ergodic Markov chains

被引:124
作者
Mitrophanov, AY [1 ]
机构
[1] Saratov NG Chernyshevskii State Univ, Saratov, Russia
关键词
Markov chain; uniform ergodicity; rate of convergence; ergodicity coefficient; perturbation bound; sensitivity analysis;
D O I
10.1239/jap/1134587812
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
For uniformly ergodic Markov chains, we obtain new perturbation bounds which relate the sensitivity of the chain under perturbation to its rate of convergence to stationarity. In particular, we derive sensitivity bounds in terms of the ergodicity coefficient of the iterated transition kernel, which improve upon the bounds obtained by other authors. We discuss convergence bounds that hold in the case of finite state space, and consider numerical examples to compare the accuracy of different perturbation bounds.
引用
收藏
页码:1003 / 1014
页数:12
相关论文
共 30 条
[1]  
Anisimov V. V., 1988, UKRANIAN MATH J, V40, P588
[2]   Comparison of perturbation bounds for the stationary distribution of a Markov chain [J].
Cho, GE ;
Meyer, CD .
LINEAR ALGEBRA AND ITS APPLICATIONS, 2001, 335 :137-150
[3]  
Diaconis P., 1991, Ann. Appl. Probab., P36
[4]  
Dobrushin R., 1956, THEOR PROBAB APPL, V1, P63
[5]  
Dobrushin RL, 1956, THEOR PROBAB APPL, V1, P329, DOI DOI 10.1137/1101029
[6]  
Fill J. A., 1991, Annals of Applied Probability, V1, P62, DOI 10.1214/aoap/1177005981
[7]  
Horn R. A., 1986, Matrix analysis
[8]   ON THE RATE OF CONVERGENCE OF THE METROPOLIS ALGORITHM AND GIBBS SAMPLER BY GEOMETRIC BOUNDS [J].
Ingrassia, Salvatore .
ANNALS OF APPLIED PROBABILITY, 1994, 4 (02) :347-389
[9]  
Kartashov N. V., 1996, Strong Stable Markov Chains, DOI [10.1515/9783110917765, DOI 10.1515/9783110917765]