The Annals of Applied Probability

Analysis of a nonreversible Markov chain sampler

Persi Diaconis, Susan Holmes, and Radford M. Neal

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We analyze the convergence to stationarity of a simple nonreversible Markov chain that serves as a model for several nonreversible Markov chain sampling methods that are used in practice. Our theoretical and numerical results show that nonreversibility can indeed lead to improvements over the diffusive behavior of simple Markov chain sampling schemes. The analysis uses both probabilistic techniques and an explicit diagonalization.

Article information

Ann. Appl. Probab., Volume 10, Number 3 (2000), 726-752.

First available in Project Euclid: 22 April 2002

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Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Primary: 60J10: Markov chains (discrete-time Markov processes on discrete state spaces)
Secondary: 65U05

Nonreversible Markov chain Markov chain Monte Carlo Metropolis algorithm


Diaconis, Persi; Holmes, Susan; Neal, Radford M. Analysis of a nonreversible Markov chain sampler. Ann. Appl. Probab. 10 (2000), no. 3, 726--752. doi:10.1214/aoap/1019487508.

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