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dc.contributor.authorRuggeri, Fabrizio
dc.contributor.authorSánchez Sánchez, Marta 
dc.contributor.authorSordo Díaz, Miguel Ángel 
dc.contributor.authorSuárez Llorens, Alfonso 
dc.contributor.otherEstadística e Investigación Operativaes_ES
dc.date.accessioned2021-02-18T08:29:52Z
dc.date.available2021-02-18T08:29:52Z
dc.date.issued2021-03
dc.identifier.issn1931-6690
dc.identifier.issn1936-0975 (internet)
dc.identifier.urihttp://hdl.handle.net/10498/24507
dc.description.abstractn the context of robust Bayesian analysis for multiparameter distributions, we introduce a new class of priors based on stochastic orders, multivariate total positivity of order 2 (MTP2) and weighted distributions. We provide the new definition, its interpretation and the main properties and we also study the relationship with other classical classes of prior beliefs. We also consider the Hellinger metric and the Kullback-Leibler divergence to measure the uncertainty induced by such a class, as well as its effect on the posterior distribution. Finally, we conclude the paper with a real example about train door reliability.es_ES
dc.formatapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherINT SOC BAYESIAN ANALYSISes_ES
dc.sourceBayesian Analysis (2021) 16, Number 1, pp. 31–60es_ES
dc.subjectrobust Bayesian analysises_ES
dc.subjectBayesian sensitivityes_ES
dc.subjectclass of priorses_ES
dc.subjectstochastic orderses_ES
dc.subjectmultivariate total positivityes_ES
dc.subjectweighted distributionses_ES
dc.titleOn a New Class of Multivariate Prior Distributions: Theory and Application in Reliabilityes_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1214/19-BA1191
dc.relation.projectIDMinisterio de Economia y Competitividad (Spain) [MTM2017-89577-P]es_ES


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