Geometric Ergodicity and Hybrid Markov Chains

Gareth O. Roberts (University of Cambridge)
Jeffrey S. Rosenthal (University of Toronto)

Abstract


Various notions of geometric ergodicity for Markov chains on general state spaces exist. In this paper, we review certain relations and implications among them. We then apply these results to a collection of chains commonly used in Markov chain Monte Carlo simulation algorithms, the so-called hybrid chains. We prove that under certain conditions, a hybrid chain will "inherit" the geometric ergodicity of its constituent parts.

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Pages: 13-25

Publication Date: May 14, 1997

DOI: 10.1214/ECP.v2-981

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