dc.creatorGarcia
dc.creatorJesus E.
dc.date2015
dc.date2016-06-07T13:23:11Z
dc.date2016-06-07T13:23:11Z
dc.date.accessioned2018-03-29T01:42:40Z
dc.date.available2018-03-29T01:42:40Z
dc.identifier978-0-7354-1287-3
dc.identifierCombining Multivariate Markov Chains. Amer Inst Physics, v. 1648, p. 2015.
dc.identifier0094-243X
dc.identifierWOS:000355339700065
dc.identifier10.1063/1.4912373
dc.identifierhttps://www.google.com.br/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwj39a6W1MPMAhUGj5AKHRDaDqMQFgggMAA&url=http%3A%2F%2Fneuromat.numec.prp.usp.br%2Frelatorio%2Fartigos%2Fgarcia_2014_2.pdf&usg=AFQjCNG57lQiVg0Miai7jSaUwOPZbVbj7w
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/243340
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1307038
dc.descriptionIn this paper we address the problem of modelling multivariate finite order Markov chains, when the dataset is not large enough to apply the usual methodology. The number of parameters needed for a multivariate Markov chain grows exponentially with the process order and dimension of the chain's alphabet. Usually, when the data set is small, the order of the fitted model is reduced compared to the true process order. In this paper we introduce a strategy to estimate a multivariate process, through this new strategy the estimated order will be greater than the order achieved using standard statistical procedures. We apply the partition Markov models, which is a family of models, where each member is identified by a partition of the state space. The procedure consist in obtaining a partition of the state space that is constructed from a combination of the partitions corresponding to the marginal processes of the multivariate chain, and the partition corresponding to the multivariate Markov chain.
dc.description1648
dc.description
dc.description
dc.description
dc.description
dc.description
dc.description
dc.description
dc.languageen
dc.publisherAMER INST PHYSICS
dc.publisher
dc.publisherMELVILLE
dc.relationPROCEEDINGS OF THE INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2014 (ICNAAM-2014)
dc.rightsembargo
dc.sourceWOS
dc.subjectSelection
dc.titleCombining Multivariate Markov Chains
dc.typeActas de congresos


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