The Annals of Applied Probability

Perfect sampling of ergodic Harris chains

J. N. Corcoran and R. L. Tweedie

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Abstract

We develop an algorithm for simulating “perfect” random samples from the invariant measure of a Harris recurrent Markov chain.The method uses backward coupling of embedded regeneration times and works most effectively for stochastically monotone chains, where paths may be sandwiched between “upper” and “lower” processes. We give an approach to finding analytic bounds on the backward coupling times in the stochastically monotone case. An application to storage models is given.

Article information

Source
Ann. Appl. Probab., Volume 11, Number 2 (2001), 438-451.

Dates
First available in Project Euclid: 5 March 2002

Permanent link to this document
https://projecteuclid.org/euclid.aoap/1015345299

Digital Object Identifier
doi:10.1214/aoap/1015345299

Mathematical Reviews number (MathSciNet)
MR1843053

Zentralblatt MATH identifier
1017.60082

Subjects
Primary: 60J10: Markov chains (discrete-time Markov processes on discrete state spaces) 60K05: Renewal theory 60K30: Applications (congestion, allocation, storage, traffic, etc.) [See also 90Bxx]

Keywords
Irreducible Markov chains invariant measures geometric ergodicity backward coupling coupling from the past exact sampling perfect sampling queues storage models

Citation

Corcoran, J. N.; Tweedie, R. L. Perfect sampling of ergodic Harris chains. Ann. Appl. Probab. 11 (2001), no. 2, 438--451. doi:10.1214/aoap/1015345299. https://projecteuclid.org/euclid.aoap/1015345299


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