Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/36413
Title: Asymptotic variance of stationary reversible and normal Markov processes
Authors: Deligiannidis, G.
Peligrad, M.
Utev, Sergey
First Published: 3-Mar-2015
Publisher: Institute of Mathematical Statistics (IMS) with Bernoulli Society for Mathematical Statistics and Probability
Citation: Electronic Journal of Probability, 2015, 20, pp. 1-26 (26)
Abstract: We obtain necessary and sufficient conditions for the regular variation of the variance of partial sums of functionals of discrete and continuous-time stationary Markov processes with normal transition operators. We also construct a class of Metropolis-Hastings algorithms which satisfy a central limit theorem and invariance principle when the variance is not linear in n.
DOI Link: 10.1214/EJP.v20-3183
ISSN: 1083-6489
Links: http://ejp.ejpecp.org/article/view/3183
http://hdl.handle.net/2381/36413
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2015, the authors. This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Appears in Collections:Published Articles, Dept. of Mathematics

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