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dc.contributor.authorBillard, Lynne
dc.contributor.authorDiday, Edwin
dc.date.accessioned2009-07-09T08:16:33Z
dc.date.available2009-07-09T08:16:33Z
dc.date.issued2006-01
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/1015
dc.language.isoenen
dc.subjectInterval-valued data ; logical dependency rules ; univariate histogrames ; sample means ; sample variances ; joint histogramen
dc.subject.ddc519en
dc.titleDescriptive Statistics for Interval-valued Observations in the presence of Rulesen
dc.typeArticle accepté pour publication ou publié
dc.contributor.editoruniversityotherUniversity of Georgia;États-Unis
dc.description.abstractenWhile symbolic data exist in their own right, contemporary datasets can be too large to analyse using traditional statistical methodologies. Aggregation of these large datasets into sets of more managable size perforce produce datasets whose entries are symbolic data. This paper studies the derivation of basic description statistics, in particular, histograms and mean and variances plus joint histograms for interval-valued datasets when logical dependency rules are present. Algorithms for calculating these histograms are also provided.
dc.relation.isversionofjnlnameComputational Statistics
dc.relation.isversionofjnlvol21en
dc.relation.isversionofjnlissue2
dc.relation.isversionofjnldate2006-10
dc.relation.isversionofjnlpages187-210en
dc.relation.isversionofdoihttp://dx.doi.org/10.1007/s00180-006-0259-6
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherSpringer
dc.subject.ddclabelProbabilités et mathématiques appliquéesen


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