Penalized estimate of the number of states in Gaussian linear AR with Markov regime

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dc.creatorRíos, Ricardo
dc.creatorRodríguez, Luis-Angel
dc.date2008-07-17
dc.date2008-11-21
dc.date.accessioned2026-07-07T10:19:38Z
dc.date.available2026-07-07T10:19:38Z
dc.descriptionWe deal with the estimation of the regime number in a linear Gaussian autoregressive process with a Markov regime (AR-MR). The problem of estimating the number of regimes in this type of series is that of determining the number of states in the hidden Markov chain controlling the process. We propose a method based on penalized maximum likelihood estimation and establish its strong consistency (almost sure) without assuming previous bounds on the number of states.
dc.descriptionPublished in at http://dx.doi.org/10.1214/08-EJS272 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/0807.2726
dc.identifierhttp://arxiv.org/abs/0807.2726
dc.identifierElectronic Journal of Statistics 2008, Vol. 2, 1111-1128
dc.identifierdoi:10.1214/08-EJS272
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/174583
dc.subjectStatistics Theory
dc.subject62F05 (Primary) 62M05 (Secondary)
dc.titlePenalized estimate of the number of states in Gaussian linear AR with Markov regime
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