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Principal component analysis for interval-valued observations

dc.contributor.authorDiday, Edwin
dc.contributor.authorDouzal-Chouakria, Ahlame
dc.contributor.authorBillard, Lynne
dc.date.accessioned2010-01-26T16:00:37Z
dc.date.available2010-01-26T16:00:37Z
dc.date.issued2011
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/3146
dc.language.isoenen
dc.subjectinertiaen
dc.subjectcorrelations
dc.subjectvertex contributions
dc.subjectvertices principal components
dc.subject.ddc519en
dc.titlePrincipal component analysis for interval-valued observationsen
dc.typeArticle accepté pour publication ou publié
dc.contributor.editoruniversityotherUniversité Joseph Fourier - Grenoble I, Grenoble;France
dc.contributor.editoruniversityotherUniversity of Georgia;États-Unis
dc.description.abstractenOne feature of contemporary datasets is that instead of the single point value in the p-dimensional space ℜp seen in classical data, the data may take interval values thus producing hypercubes in ℜp. This paper studies the vertices principal components methodology for interval-valued data; and provides enhancements to allow for so-called ‘trivial’ intervals, and generalized weight functions. It also introduces the concept of vertex contributions to the underlying principal components, a concept not possible for classical data, but one which provides a visualization method that further aids in the interpretation of the methodology. The method is illustrated in a dataset using measurements of facial characteristics obtained from a study of face recognition patterns for surveillance purposes. A comparison with analyses in which classical surrogates replace the intervals, shows how the symbolic analysis gives more informative conclusions. A second example illustrates how the method can be applied even when the number of parameters exceeds the number of observations, as well as how uncertainty data can be accommodated.en
dc.relation.isversionofjnlnameStatistical Analysis and Data Mining
dc.relation.isversionofjnlvol4
dc.relation.isversionofjnlissue2
dc.relation.isversionofjnldate2011
dc.relation.isversionofjnlpages229-246
dc.relation.isversionofdoihttp://dx.doi.org/10.1002/sam.10118
dc.identifier.urlsitehttp://hal.archives-ouvertes.fr/hal-00361053en
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherWiley
dc.subject.ddclabelProbabilités et mathématiques appliquéesen


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