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Efficiency of finite state space Monte Carlo Markov chains

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  • Mira, Antonietta

Abstract

The class of finite state space Markov chains, stationary with respect to a common pre-specified distribution, is considered. An easy-to-check partial ordering is defined on this class. The ordering provides a sufficient condition for the dominating Markov chain to be more efficient. Efficiency is measured by the asymptotic variance of the estimator of the integral of a specific function with respect to the stationary distribution of the chains. A class of transformations that, when applied to a transition matrix, preserves its stationary distribution and improves its efficiency is defined and studied.

Suggested Citation

  • Mira, Antonietta, 2001. "Efficiency of finite state space Monte Carlo Markov chains," Statistics & Probability Letters, Elsevier, vol. 54(4), pages 405-411, October.
    • Handle: RePEc:eee:stapro:v:54:y:2001:i:4:p:405-411
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    Cited by:

    1. Hwang, Chii-Ruey & Normand, Raoul & Wu, Sheng-Jhih, 2015. "Variance reduction for diffusions," Stochastic Processes and their Applications, Elsevier, vol. 125(9), pages 3522-3540.

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