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dc.rights.licenseAtribución-NoComercial 4.0 Internacional
dc.contributor.authorCepeda Cuervo, Edilberto
dc.date.accessioned2019-06-24T21:04:37Z
dc.date.available2019-06-24T21:04:37Z
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/9659
dc.description.abstractIn this paper WinBugs code to fit joint mean and precision (variance) beta regression models is presented. These models are fitted applying Bayesian methodology and assuming normal prior distribution for the regression parameters. Analysis of structural data are included, assuming these models.
dc.format.mimetypeapplication/pdf
dc.language.isospa
dc.relation.ispartofUniversidad Nacional de Colombia Sede Bogotá Facultad de Ciencias Departamento de Estadística
dc.relation.ispartofDepartamento de Estadística
dc.rightsDerechos reservados - Universidad Nacional de Colombia
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subject.ddc31 Colecciones de estadística general / Statistics
dc.subject.ddc51 Matemáticas / Mathematics
dc.titleWinBugs CODE for Beta Regression Models
dc.typeDocumento de trabajo
dc.type.driverinfo:eu-repo/semantics/workingPaper
dc.type.versioninfo:eu-repo/semantics/draft
dc.identifier.eprintshttp://bdigital.unal.edu.co/6610/
dc.relation.referencesCepeda Cuervo, Edilberto WinBugs CODE for Beta Regression Models. Reporte técnico. Sin Definir. (No publicado)
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.subject.proposalBeta regression models, WinBugs CODE, Bayesian methodology
dc.type.coarhttp://purl.org/coar/resource_type/c_8042
dc.type.coarversionhttp://purl.org/coar/version/c_b1a7d7d4d402bcce
dc.type.contentText
dc.type.redcolhttp://purl.org/redcol/resource_type/WP
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2


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Atribución-NoComercial 4.0 InternacionalThis work is licensed under a Creative Commons Reconocimiento-NoComercial 4.0.This document has been deposited by the author (s) under the following certificate of deposit