Bayesian inference for random partitions

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dc.contributor.advisorMüller, Peter, 1963 August 9-
dc.creatorSundar, Radhikaen
dc.date.accessioned2013-12-05T18:14:46Zen
dc.date.accessioned2017-05-11T22:39:42Z
dc.date.available2017-05-11T22:39:42Z
dc.date.issued2013-08en
dc.date.submittedAugust 2013en
dc.date.updated2013-12-05T18:14:46Zen
dc.descriptiontexten
dc.description.abstractI consider statistical inference for clustering, that is the arrangement of experimental units in homogeneous groups. In particular, I discuss clustering for multivariate binary outcomes. Binary data is not very informative, making it less meaningful to proceed with traditional (deterministic) clustering methods. Meaningful inference needs to account for and report the considerable uncertainty related with any reported cluster arrangement. I review and implement an approach that was proposed in the recent literature.en
dc.description.departmentStatisticsen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/2152/22565en
dc.language.isoen_USen
dc.subjectBayesianen
dc.subjectSubset clusteringen
dc.titleBayesian inference for random partitionsen

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