dc.creatorCabral, CRB
dc.creatorLachos, VH
dc.creatorPrates, MO
dc.date2012
dc.date36892
dc.date2014-08-01T18:40:25Z
dc.date2015-11-26T17:08:31Z
dc.date2014-08-01T18:40:25Z
dc.date2015-11-26T17:08:31Z
dc.date.accessioned2018-03-28T23:57:10Z
dc.date.available2018-03-28T23:57:10Z
dc.identifierComputational Statistics & Data Analysis. Elsevier Science Bv, v. 56, n. 1, n. 126, n. 142, 2012.
dc.identifier0167-9473
dc.identifierWOS:000295436200011
dc.identifier10.1016/j.csda.2011.06.026
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/82056
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/82056
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1280389
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionIn this paper we consider a flexible class of models, with elements that are finite mixtures of multivariate skew-normal independent distributions. A general EM-type algorithm is employed for iteratively computing parameter estimates and this is discussed with emphasis on finite mixtures of skew-normal, skew-t, skew-slash and skew-contaminated normal distributions. Further, a general information-based method for approximating the asymptotic covariance matrix of the estimates is also presented. The accuracy of the associated estimates and the efficiency of some information criteria are evaluated via simulation studies. Results obtained from the analysis of artificial and real data sets are reported illustrating the usefulness of the proposed methodology. The proposed EM-type algorithm and methods are implemented in the R package mixsmsn. (C) 2011 Elsevier B.V. All rights reserved.
dc.description56
dc.description1
dc.description126
dc.description142
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionCNPq [308109/2008-2]
dc.descriptionFAPESP [2008/11455-0, 2011/01437-8]
dc.languageen
dc.publisherElsevier Science Bv
dc.publisherAmsterdam
dc.publisherHolanda
dc.relationComputational Statistics & Data Analysis
dc.relationComput. Stat. Data Anal.
dc.rightsfechado
dc.rightshttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dc.sourceWeb of Science
dc.subjectEM algorithm
dc.subjectMultivariate finite mixtures
dc.subjectSkew-normal distribution
dc.subjectSkew-normal independent distributions
dc.subjectMaximum-likelihood-estimation
dc.subjectT-distribution
dc.subjectFinite Mixtures
dc.subjectScale Mixtures
dc.subjectEm Algorithm
dc.subjectRobust
dc.subjectIdentifiability
dc.subjectConvergence
dc.subjectExtension
dc.subjectInference
dc.titleMultivariate mixture modeling using skew-normal independent distributions
dc.typeArtículos de revistas


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