Subgeometric rates of convergence for a class of continuous-time Markov process

被引:12
作者
Hou, ZT [1 ]
Liu, YY
Zhang, HJ
机构
[1] Cent S Univ, Sch Math, Changsha 410075, Hunan, Peoples R China
[2] Univ Queensland, Dept Math, Brisbane, Qld 4072, Australia
关键词
continuous-time Markov process; queueing model; birth-death process; ergodicity; subgeometric convergence;
D O I
10.1239/jap/1127322021
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
Let (Phi(t))(t is an element of R+) be a Harris ergodic continuous-time Markov process on a general state space, with invariant probability measure pi. We investigate the rates of convergence of the transition function P-t(x, (.)) to pi; specifically, we find conditions under which r(t) vertical bar vertical bar P-t (x, (.)) - pi vertical bar vertical bar -> 0 as t -> infinity, for suitable subgeometric rate functions r(t), where vertical bar vertical bar - vertical bar vertical bar denotes the usual total variation norm for a signed measure. We derive sufficient conditions for the convergence to hold, in terms of the existence of suitable points on which the first hitting time moments are bounded. In particular, for stochastically ordered Markov processes, explicit bounds on subgeometric rates of convergence are obtained. These results are illustrated in several examples.
引用
收藏
页码:698 / 712
页数:15
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