Variance bounding Markov chains

dc.creatorRoberts, Gareth O.
dc.creatorRosenthal, Jeffrey S.
dc.date2008-06-17
dc.date.accessioned2026-07-07T12:19:34Z
dc.date.available2026-07-07T12:19:34Z
dc.descriptionWe introduce a new property of Markov chains, called variance bounding. We prove that, for reversible chains at least, variance bounding is weaker than, but closely related to, geometric ergodicity. Furthermore, variance bounding is equivalent to the existence of usual central limit theorems for all $L^2$ functionals. Also, variance bounding (unlike geometric ergodicity) is preserved under the Peskun order. We close with some applications to Metropolis--Hastings algorithms.
dc.descriptionPublished in at http://dx.doi.org/10.1214/07-AAP486 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0806.2747
dc.identifierhttp://arxiv.org/abs/0806.2747
dc.identifierAnnals of Applied Probability 2008, Vol. 18, No. 3, 1201-1214
dc.identifierdoi:10.1214/07-AAP486
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/212799
dc.subjectProbability
dc.subject60J10 (Primary) 65C40, 47A10 (Secondary)
dc.titleVariance bounding Markov chains
dc.typetext

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