Bayesian mixture of parametric and nonparametric density estimation: A Misspecification Problem

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dc.contributor.authorHEDIBERT FREITAS LOPES
dc.contributor.authorDias, Ronaldo
dc.coverage.cidadeNão informadopt_BR
dc.coverage.paisBrasilpt_BR
dc.creatorDias, Ronaldo
dc.date.accessioned2022-08-18T18:19:29Z
dc.date.available2022-08-18T18:19:29Z
dc.date.issued2011
dc.description.otherIn this paper we study the effect of model misspecifications for probability density func tion estimation. We use a mixture of a parametric and nonparametric density estima tion. The former can be modeled by any suitable parametric probability density function, including mixture of parametric models. The latter is given by the known B-spline es timation. The procedure also deals with the situation when a highly structured data are collected so that it is difficult to propose a parametric model with a large number of mixture components. Then a nonparametric part would help to postulate an appropriate model. In addition, in order to reduce the computational cost of getting a nonparamet ric density for high dimensional data a parametric mixture of densities could be used as the starting point for modeling such dataset. Our procedure is computed by using EM-type algorithm for a non-Bayesian approach and MCMC algorithm under a Bayesian point of view. Simulations and real data analysis show that our proposed procedure have performed quite well even for non structured datasets.pt_BR
dc.format.extent26 p.pt_BR
dc.format.mediumDigitalpt_BR
dc.identifier.doihttps://doi.org/10.12660/bre.v31n12011.4134pt_BR
dc.identifier.issue1pt_BR
dc.identifier.urihttps://repositorio.insper.edu.br/handle/11224/4042
dc.identifier.volume31pt_BR
dc.language.isoInglêspt_BR
dc.publisherNão informadopt_BR
dc.relation.ispartofBrazilian Review of Econometricspt_BR
dc.rights.licenseO INSPER E ESTE REPOSITÓRIO NÃO DETÊM OS DIREITOS DE USO E REPRODUÇÃO DOS CONTEÚDOS AQUI REGISTRADOS. É RESPONSABILIDADE DOS USUÁRIOS INDIVIDUAIS VERIFICAR OS USOS PERMITIDOS NA FONTE ORIGINAL, RESPEITANDO-SE OS DIREITOS DE AUTOR OU EDITOR.pt_BR
dc.subject.keywordsNonparametric Density Estimationpt_BR
dc.subject.keywordsB-Splinespt_BR
dc.subject.keywordsMixtures Modelspt_BR
dc.subject.keywordsMCMCpt_BR
dc.subject.keywordsEM-Algortihmpt_BR
dc.titleBayesian mixture of parametric and nonparametric density estimation: A Misspecification Problempt_BR
dc.typejournal article
dspace.entity.typePublication
local.identifier.sourceUrihttps://bibliotecadigital.fgv.br/ojs/index.php/bre/article/view/4134
local.subject.cnpqCiências Sociais Aplicadaspt_BR
local.typeArtigo Científicopt_BR
relation.isAuthorOfPublication41f844cb-0e5a-4ef1-bb19-5ab1cec8e2ca
relation.isAuthorOfPublication.latestForDiscovery41f844cb-0e5a-4ef1-bb19-5ab1cec8e2ca

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