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.Official URL: http://dx.doi.org/10.1239/jap/1014842542
Abstract
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.
| Item Type: | Article |
|---|---|
| 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 |
| ID Code: | 19367 |
| Deposited By: | ep_ss_importer |
| Deposited On: | 20 Nov 2008 14:15 |
| Refereed?: | Yes |
| Published?: | Published |
| Last Modified: | 26 Jul 2012 15:28 |
| Identification Number: | |
| URI: | http://eprints.lancs.ac.uk/id/eprint/19367 |
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