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Discussion on the paper by Peter Muller, Fernando A. Quintana, and Garritt L. Page

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dc.contributor.authorJo, Seongil-
dc.contributor.authorLee, Jaeyong-
dc.date.accessioned2023-10-30T01:50:58Z-
dc.date.available2023-10-30T01:50:58Z-
dc.date.created2019-03-20-
dc.date.issued2018-06-
dc.identifier.citationStatistical Methods and Applications, Vol.27 No.2, pp.227-230-
dc.identifier.issn1618-2510-
dc.identifier.urihttps://hdl.handle.net/10371/195916-
dc.description.abstractThe article by Muller, Quintana, and Page reviews a variety of Bayesian nonparametric models and demonstrates them in a few applications. They emphasize applications in spatial data on which our discussion focuses as well. In particular, we consider two types of mixture models based on species sampling models (SSM) for spatial clustering and apply them to the Chilean mathematics testing score data analyzed by the authors. We conclude that only the mixture model of SSM with spatial locations as part of observations renders spatially non-overlapping clusters.-
dc.language영어-
dc.publisherSpringer Verlag-
dc.titleDiscussion on the paper by Peter Muller, Fernando A. Quintana, and Garritt L. Page-
dc.typeArticle-
dc.identifier.doi10.1007/s10260-017-0396-9-
dc.citation.journaltitleStatistical Methods and Applications-
dc.identifier.wosid000433538700004-
dc.identifier.scopusid2-s2.0-85028980896-
dc.citation.endpage230-
dc.citation.number2-
dc.citation.startpage227-
dc.citation.volume27-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorLee, Jaeyong-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.subject.keywordPlusSPECIES SAMPLING MODELS-
dc.subject.keywordAuthorSpatial clustering-
dc.subject.keywordAuthorSpatial correlation structure-
dc.subject.keywordAuthorSpecies sampling mixture models-
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