Roberts, G. O. and Tweedie, R. L. (2000) Rates of convergence of stochastically monotone and continuous time Markov models. Journal of Applied Probability, 37 (2). pp. 359-373.Full text not available from this repository.
In this paper we give bounds on the total variation distance from convergence of a continuous time positive recurrent Markov process on an arbitrary state space, based on Foster-Lyapunov drift and minorisation conditions. Considerably improved bounds are given in the stochastically monotone case, for both discrete and continuous time models, even in the absence of a reachable minimal element. These results are applied to storage models and to diffusion processes.
|Journal or Publication Title:||Journal of Applied Probability|
|Uncontrolled Keywords:||Stochastic monotonicity ; rates of convergence ; Markov chain ; Markov process|
|Subjects:||Q Science > QA Mathematics|
|Departments:||Faculty of Science and Technology > Lancaster Environment Centre|
|Deposited On:||20 Nov 2008 14:15|
|Last Modified:||29 Mar 2017 01:16|
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