Exponential and uniform ergodicity of Markov processes

被引:228
作者
Down, D [1 ]
Meyn, SP [1 ]
Tweedie, RL [1 ]
机构
[1] COLORADO STATE UNIV,DEPT STAT,FT COLLINS,CO 80523
关键词
convergence rates; irreducible Markov processes; geometric ergodicity; Lyapunov functions; drift conditions; resolvents; generators;
D O I
10.1214/aop/1176987798
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
General characterizations of geometric convergence for Markov chains in discrete time on a general state space have been developed recently in considerable detail. Here we develop a similar theory for phi-irreducible continuous time processes and consider the following types of criteria for geometric convergence: 1. the existence of exponentially bounded hitting times on one and then all suitably ''small'' sets; 2. the existence of ''Foster-Lyapunov'' or ''drift'' conditions for any one and then all skeleton and resolvent chains; 3. the existence of drift, conditions on the extended generator (A) over tilde of the process. We use the identity (A) over tilde R(beta) = beta(R(beta) - I) connecting the extended generator and the resolvent kernels Rp to show that, under a suitable aperiodicity assumption, exponential convergence is completely equivalent to any of criteria 1-3. These conditions yield criteria for exponential convergence of unbounded as well as bounded functions of the chain. They enable us to identify the dependence of the convergence on the initial state of the chain and also to illustrate that in general some smoothing is required to ensure convergence of unbounded functions.
引用
收藏
页码:1671 / 1691
页数:21
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