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Abstract: I propose a convergence diagnostic for Markov chain Monte Carlo (MCMC) algorithms based on couplings of a Markov chain with an auxiliary chain that is periodically restarted from a fixed parameter value. The diagnostic provides a mechanism for estimating the specific constants governing the rate of convergence of geometrically and uniformly ergodic chains, and provides a lower bound on the effective sample size of a MCMC run. It also provides a simple procedure for obtaining what is,... (Update)
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BibTeX entry: (Update)
Johnson, V. E. (1996) A coupling-regeneration scheme for diagnosing convergence in markov chain monte carlo algorithms, Technical Report 96-05, Institute of Statistics and Decision Sciences, Duke University. http://citeseer.ist.psu.edu/johnson96couplingregeneration.html More
@article{ johnson98couplingregeneration,
author = "Valen E. Johnson",
title = "A Coupling-Regeneration Scheme for Diagnosing Convergence in {Markov} Chain {Monte Carlo} Algorithms",
journal = "Journal of the American Statistical Association",
volume = "93",
number = "441",
pages = "238--248",
year = "1998",
url = "citeseer.ist.psu.edu/johnson96couplingregeneration.html" }
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Documents on the same site (http://www.stat.duke.edu/~valen/):
Posterior Distributions on Normalizing Constants - Johnson (1999) (Correct)
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