Bayesian inference in spherical linear models: robustness and conjugate analysis

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dc.contributor.authorArellano Valle, RB
dc.contributor.authordel Pino, G
dc.contributor.authorIglesias, P
dc.date.accessioned2024-01-10T13:46:21Z
dc.date.available2024-01-10T13:46:21Z
dc.date.issued2006
dc.description.abstractThe early work of Zellner on the multivariate Student-t linear model has been extended to Bayesian inference for linear models with dependent non-normal error terms, particularly through various papers by Osiewalski, Steel and coworkers. This article provides a full Bayesian analysis for a spherical linear model. The density generator of the spherical distribution is here allowed to depend both on the precision parameter phi and on the regression coefficients beta. Another distinctive aspect of this paper is that proper priors for the precision parameter are discussed.
dc.description.abstractThe normal-chi-squared family of prior distributions is extended to a new class, which allows the posterior analysis to be carried out analytically. On the other hand, a direct joint modelling of the data vector and of the parameters leads to conjugate distributions for the regression and the precision parameters, both individually and jointly. It is shown that some model specifications lead to Bayes estimators that do not depend on the choice of the density generator, in agreement with previous results obtained in the literature under different assumptions. Finally, the distribution theory developed to tackle the main problem is useful on its own right. (c) 2005 Elsevier Inc. All rights reserved.
dc.fechaingreso.objetodigital17-04-2024
dc.format.extent19 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1016/j.jmva.2004.12.002
dc.identifier.issn0047-259X
dc.identifier.urihttps://doi.org/10.1016/j.jmva.2004.12.002
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/79150
dc.identifier.wosidWOS:000233778900008
dc.information.autorucMatemática;Arellano-Valle R;S/I;58107
dc.information.autorucMatemática;Del Pino G;S/I;99446
dc.information.autorucMatemática;Iglesias P;S/I;100265
dc.issue.numero1
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final197
dc.pagina.inicio179
dc.publisherELSEVIER INC
dc.revistaJOURNAL OF MULTIVARIATE ANALYSIS
dc.rightsacceso restringido
dc.subjectlinear regression models
dc.subjectelliptical and squared-radial distributions
dc.subjectelliptical density generator
dc.subjectdispersion and dispersion-location elliptical models
dc.subjectBayes estimator
dc.subjectconjugate families
dc.subjectELLIPTIC REGRESSION-MODELS
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleBayesian inference in spherical linear models: robustness and conjugate analysis
dc.typeartículo
dc.volumen97
sipa.codpersvinculados58107
sipa.codpersvinculados99446
sipa.codpersvinculados100265
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
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