Efficiency of finite state space Monte Carlo Markov chains

Antonietta Mira

Statistics & Probability Letters, 2001, vol. 54, issue 4, 405-411

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.

Keywords: Efficiency; ordering; Markov; chain; Monte; Carlo; Metropolis-Hastings; algorithm; Peskun; ordering; Stationarity; preserving; and; efficiency; increasing; probability; mass; transfers (search for similar items in EconPapers)
Date: 2001
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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