The Annals of Applied Probability

Perfect simulation for a class of positive recurrent Markov chains

Stephen B. Connor and Wilfrid S. Kendall

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This paper generalizes the work of Kendall [Electron. Comm. Probab. 9 (2004) 140–151], which showed that perfect simulation, in the form of dominated coupling from the past, is always possible (although not necessarily practical) for geometrically ergodic Markov chains. Here, we consider the more general situation of positive recurrent chains and explore when it is possible to produce such a simulation algorithm for these chains. We introduce a class of chains which we name tame, for which we show that perfect simulation is possible.

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Ann. Appl. Probab., Volume 17, Number 3 (2007), 781-808.

First available in Project Euclid: 22 May 2007

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Zentralblatt MATH identifier

Primary: 60J65: Brownian motion [See also 58J65] 65C05: Monte Carlo methods 68U20: Simulation [See also 65Cxx]

CFTP domCFTP polynomial ergodicity Foster–Lyapunov condition Markov chain Monte Carlo perfect simulation


Connor, Stephen B.; Kendall, Wilfrid S. Perfect simulation for a class of positive recurrent Markov chains. Ann. Appl. Probab. 17 (2007), no. 3, 781--808. doi:10.1214/105051607000000032.

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