Coupling and Ergodicity of Adaptive Markov Chain Monte Carlo Algorithms-Reference-Cited by-同舟云学术

Coupling and Ergodicity of Adaptive Markov Chain Monte Carlo Algorithms

Published:2007-06 Issue:2 Volume:44 Page:458-475
ISSN:0021-9002
Container-title:Journal of Applied Probability
language:en
Short-container-title:Journal of Applied Probability

Author:

Roberts Gareth O.,Rosenthal Jeffrey S.

Abstract

We consider basic ergodicity properties of adaptive Markov chain Monte Carlo algorithms under minimal assumptions, using coupling constructions. We prove convergence in distribution and a weak law of large numbers. We also give counterexamples to demonstrate that the assumptions we make are not redundant.

Publisher

Cambridge University Press (CUP)

Subject

Statistics, Probability and Uncertainty,General Mathematics,Statistics and Probability

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