ECP Reading Tools

Geometric Ergodicity and Hybrid Markov Chains

Dublin Core		PKP Metadata Items	Metadata for this Document
1.	Title	Title of document	Geometric Ergodicity and Hybrid Markov Chains
2.	Creator	Author's name, affiliation, country	Gareth O. Roberts; University of Cambridge
2.	Creator	Author's name, affiliation, country	Jeffrey S. Rosenthal; University of Toronto
3.	Subject	Discipline(s)
3.	Subject	Keyword(s)	Markov chain Monte Carlo, hybrid Monte Carlo, geometric ergodicity, reversibility, spectral gap.
3.	Subject	Subject classification	60J25
4.	Description	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.
5.	Publisher	Organizing agency, location
6.	Contributor	Sponsor(s)
7.	Date	(YYYY-MM-DD)	1997-05-14
8.	Type	Status & genre	Peer-reviewed Article
8.	Type	Type
9.	Format	File format	PDF
10.	Identifier	Uniform Resource Identifier	http://ecp.ejpecp.org/article/view/981
10.	Identifier	Digital Object Identifier	10.1214/ECP.v2-981
11.	Source	Journal/conference title; vol., no. (year)	Electronic Communications in Probability; Vol 2
12.	Language	English=en
14.	Coverage	Geo-spatial location, chronological period, research sample (gender, age, etc.)
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