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Rates of convergence of stochastically monotone and continuous time Markov models

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Rates of convergence of stochastically monotone and continuous time Markov models. / Roberts, G. O.; Tweedie, R. L.
In: Journal of Applied Probability, Vol. 37, No. 2, 2000, p. 359-373.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Roberts, GO & Tweedie, RL 2000, 'Rates of convergence of stochastically monotone and continuous time Markov models', Journal of Applied Probability, vol. 37, no. 2, pp. 359-373. https://doi.org/10.1239/jap/1014842542

APA

Roberts, G. O., & Tweedie, R. L. (2000). Rates of convergence of stochastically monotone and continuous time Markov models. Journal of Applied Probability, 37(2), 359-373. https://doi.org/10.1239/jap/1014842542

Vancouver

Roberts GO, Tweedie RL. Rates of convergence of stochastically monotone and continuous time Markov models. Journal of Applied Probability. 2000;37(2):359-373. doi: 10.1239/jap/1014842542

Author

Roberts, G. O. ; Tweedie, R. L. / Rates of convergence of stochastically monotone and continuous time Markov models. In: Journal of Applied Probability. 2000 ; Vol. 37, No. 2. pp. 359-373.

Bibtex

@article{f408b5f7805844a6bbc7e8ca1f86e219,
title = "Rates of convergence of stochastically monotone and continuous time Markov models",
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.",
keywords = "Stochastic monotonicity, rates of convergence, Markov chain, Markov process",
author = "Roberts, {G. O.} and Tweedie, {R. L.}",
year = "2000",
doi = "10.1239/jap/1014842542",
language = "English",
volume = "37",
pages = "359--373",
journal = "Journal of Applied Probability",
publisher = "University of Sheffield",
number = "2",

}

RIS

TY - JOUR

T1 - Rates of convergence of stochastically monotone and continuous time Markov models

AU - Roberts, G. O.

AU - Tweedie, R. L.

PY - 2000

Y1 - 2000

N2 - 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.

AB - 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.

KW - Stochastic monotonicity

KW - rates of convergence

KW - Markov chain

KW - Markov process

U2 - 10.1239/jap/1014842542

DO - 10.1239/jap/1014842542

M3 - Journal article

VL - 37

SP - 359

EP - 373

JO - Journal of Applied Probability

JF - Journal of Applied Probability

IS - 2

ER -