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Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/9928
DC FieldValueLanguage
dc.contributor.authorKolossiatis, Michalis-
dc.contributor.authorGriffin, Jim E.-
dc.contributor.authorSteel, Mark F J-
dc.date.accessioned2017-02-24T08:48:10Z-
dc.date.available2017-02-24T08:48:10Z-
dc.date.issued2013-
dc.identifier.citationStatistics and Computing, 2013, vol. 23, no. 1, pp. 1-15en_US
dc.identifier.issn15731375-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/9928-
dc.description.abstractIn this paper, we consider the problem of modelling a pair of related distributions using Bayesian nonparametric methods. A representation of the distributions as weighted sums of distributions is derived through normalisation. This allows us to define several classes of nonparametric priors. The properties of these distributions are explored and efficient Markov chain Monte Carlo methods are developed. The methodology is illustrated on simulated data and an example concerning hospital efficiency measurement.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofStatistics and Computingen_US
dc.rights© Springeren_US
dc.subjectDependent Dirichlet processen_US
dc.subjectMarkov chain Monte Carloen_US
dc.subjectNormalised random measuresen_US
dc.subjectPólya-urn schemeen_US
dc.subjectSplit-merge moveen_US
dc.titleOn Bayesian nonparametric modelling of two correlated distributionsen_US
dc.typeArticleen_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationUniversity of Kent at Canterburyen_US
dc.collaborationUniversity of Warwicken_US
dc.subject.categoryMathematicsen_US
dc.journalsSubscriptionen_US
dc.countryCyprusen_US
dc.countryUnited Kingdomen_US
dc.subject.fieldNatural Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1007/s11222-011-9283-7en_US
dc.relation.issue1en_US
dc.relation.volume23en_US
cut.common.academicyear2012-2013en_US
dc.identifier.spage1en_US
dc.identifier.epage15en_US
item.openairetypearticle-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.grantfulltextnone-
crisitem.journal.journalissn1573-1375-
crisitem.journal.publisherSpringer Nature-
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