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Covariance Ordering for discrete and continuous time Markov Chains

Mira, Antonietta, Leisen, Fabrizio (2009) Covariance Ordering for discrete and continuous time Markov Chains. Statistica Sinica, 19 (2). pp. 651-666. ISSN 1017-0405. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://www3.stat.sinica.edu.tw/statistica/j19n2/j1...

Abstract

The covariance ordering, for discrete and continuous time Markov chains, is defined and studied. This partial ordering gives a necessary and sufficient condition for MCMC estimators to have small asymptotic variance. Connections between this ordering, eigenvalues, and suprema of the spectrum of the Markov transition kernel, are provided. A representation of the asymptotic variance of MCMC estimators in terms of eigenvalues and eigenvectors is extended to continuous time. This representation is used to establish convergence of the asymptotic variance of MCMC estimators derived from the discretization of a continuous time Markov chain.

Item Type: Article
Uncontrolled keywords: Asymptotic variance, efficiency ordering, MCMC, time-invariance estimating equations.
Subjects: H Social Sciences > HA Statistics
Q Science > QA Mathematics (inc Computing science) > QA273 Probabilities
Divisions: Faculties > Sciences > School of Mathematics Statistics and Actuarial Science
Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Fabrizio Leisen
Date Deposited: 24 Dec 2013 14:01 UTC
Last Modified: 01 Aug 2019 10:36 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/37694 (The current URI for this page, for reference purposes)
Leisen, Fabrizio: https://orcid.org/0000-0002-2460-6176
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