Construction of weakly CUD sequences for MCMC sampling

Simple item page
dc.creatorTribble, Seth D.
dc.creatorOwen, Art B.
dc.date2008-07-30
dc.date.accessioned2026-07-07T09:53:44Z
dc.date.available2026-07-07T09:53:44Z
dc.descriptionIn Markov chain Monte Carlo (MCMC) sampling considerable thought goes into constructing random transitions. But those transitions are almost always driven by a simulated IID sequence. Recently it has been shown that replacing an IID sequence by a weakly completely uniformly distributed (WCUD) sequence leads to consistent estimation in finite state spaces. Unfortunately, few WCUD sequences are known. This paper gives general methods for proving that a sequence is WCUD, shows that some specific sequences are WCUD, and shows that certain operations on WCUD sequences yield new WCUD sequences. A numerical example on a 42 dimensional continuous Gibbs sampler found that some WCUD inputs sequences produced variance reductions ranging from tens to hundreds for posterior means of the parameters, compared to IID inputs.
dc.descriptionPublished in at http://dx.doi.org/10.1214/07-EJS162 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0807.4858
dc.identifierhttp://arxiv.org/abs/0807.4858
dc.identifierElectronic Journal of Statistics 2008, Vol. 2, 634-660
dc.identifierdoi:10.1214/07-EJS162
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/166063
dc.subjectComputation
dc.subjectStatistics Theory
dc.subject62F15 (Primary) 11K45, 11K41 (Secondary)
dc.titleConstruction of weakly CUD sequences for MCMC sampling
dc.typetext

Files

Collections

arXiv