Bayesian Modeling of Censored Partial Linear Models using Scale-Mixtures of Normal Distributions

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dc.contributor.authorCastro, Luis M.
dc.contributor.authorLachos, Victor H.
dc.contributor.authorFerreira, Guillermo P.
dc.contributor.authorArellano Valle, Reinaldo B.
dc.contributor.authorStern, JM
dc.contributor.authorLauretto, MD
dc.contributor.authorPolpo, A
dc.contributor.authorDiniz, MA
dc.date.accessioned2024-01-10T14:24:02Z
dc.date.available2024-01-10T14:24:02Z
dc.date.issued2012
dc.description.abstractRegression models where the dependent variable is censored (limited) are usually considered in statistical analysis. Particularly, the case of a truncation to the left of zero and a normality assumption for the error terms is studied in detail by [1] in the well known Tobit model. In the present article, this typical censored regression model is extended by considering a partial linear model with errors belonging to the class of scale mixture of normal distributions. We achieve a fully Bayesian inference by adopting a Metropolis algorithm within a Gibbs sampler. The likelihood function is utilized to compute not only some Bayesian model selection measures but also to develop Bayesian case-deletion influence diagnostics based on the q-divergence measures. We evaluate the performances of the proposed methods with simulated data. In addition, we present an application in order to know what type of variables affect the income of housewives.
dc.description.funderChilean government
dc.description.funderConselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq-Brazil)
dc.description.funderFundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP-Brazil)
dc.fechaingreso.objetodigital2024-05-02
dc.format.extent12 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1063/1.4759591
dc.identifier.eisbn978-0-7354-1102-9
dc.identifier.issn0094-243X
dc.identifier.urihttps://doi.org/10.1063/1.4759591
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/80173
dc.identifier.wosidWOS:000310688900008
dc.information.autorucFacultad de Matemáticas; Castro Cepero, Luis Mauricio; S/I; 151425
dc.language.isoen
dc.nota.accesoSin adjunto
dc.pagina.final86
dc.pagina.inicio75
dc.publisherAMER INST PHYSICS
dc.relation.ispartof11th Brazilian Meeting on Bayesian Statistics (EBEB), MAR 18-22, 2012, Amparo, BRAZIL
dc.rightsregistro bibliográfico
dc.subjectBayesian modeling
dc.subjectLimited dependent variable
dc.subjectNon-linear regression model
dc.subjectScale mixtures of normal distributions
dc.subjectTobit model
dc.subjectSENSITIVITY
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleBayesian Modeling of Censored Partial Linear Models using Scale-Mixtures of Normal Distributions
dc.typecomunicación de congreso
dc.volumen1490
sipa.codpersvinculados151425
sipa.indexWOS
sipa.trazabilidadCarga SIPA;09-01-2024
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