Bayesian inference for the half-normal and half-t distributions

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Show simple item record Wiper, Michael Peter Giron, F.J. Pewsey, A. 2006-11-09T10:58:06Z 2006-11-09T10:58:06Z 2005-07
dc.description.abstract In this article we consider approaches to Bayesian inference for the half-normal and half-t distributions. We show that a generalized version of the normal-gamma distribution is conjugate to the half-normal likelihood and give the moments of this new distribution. The bias and coverage of the Bayesian posterior mean estimator of the halfnormal location parameter are compared with those of maximum likelihood based estimators. Inference for the half-t distribution is performed using Gibbs sampling and model comparison is carried out using Bayes factors. A real data example is presented which demonstrates the fitting of the half-normal and half-t models.
dc.format.extent 798216 bytes
dc.format.mimetype application/pdf
dc.language.iso eng
dc.language.iso eng
dc.relation.ispartofseries UC3M Working Papers. Statistics and Econometrics
dc.relation.ispartofseries 2005-09
dc.title Bayesian inference for the half-normal and half-t distributions
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.identifier.repec ws054709
dc.affiliation.dpto UC3M. Departamento de Estadística
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