An exploratory canonical analysis approach for multinomial populations based on the phi-divergence measure

dc.contributor.authorPardo, J. A.en
dc.contributor.authorPardo, L.en
dc.contributor.authorPardo, M. C.en
dc.contributor.authorZografos, K.en
dc.date.accessioned2015-11-24T17:27:48Z
dc.date.available2015-11-24T17:27:48Z
dc.identifier.issn0023-5954-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/13450
dc.rightsDefault Licence-
dc.subjectcanonical analysisen
dc.subjectrestricted minimum phi-divergence estimatoren
dc.subjectminimum phi-divergence statisticen
dc.subjectsimulationen
dc.subjectpower divergenceen
dc.subjectmaximum-likelihood-estimationen
dc.subjectminimum disparity estimationen
dc.subjectloglinear modelsen
dc.subjectrobustnessen
dc.subjectefficiencyen
dc.subjectdistributionsen
dc.subjectconstraintsen
dc.subjectdistanceen
dc.subjecttermsen
dc.titleAn exploratory canonical analysis approach for multinomial populations based on the phi-divergence measureen
heal.abstractIn this paper we consider an exploratory canonical analysis approach for multinomial population based on the phi-divergence measure. We define the restricted minimum phi-divergence estimator, which is seen to be a generalization of the restricted maximum likelihood estimator. This estimator is then used in phi-divergence goodness-of-fit statistics which is the basis of two new families of statistics for solving the problem of selecting the number of significant correlations as well as the appropriateness of the model.en
heal.accesscampus-
heal.fullTextAvailabilityTRUE-
heal.identifier.secondary<Go to ISI>://000227723700009-
heal.journalNameKybernetikaen
heal.journalTypepeer reviewed-
heal.languageen-
heal.publicationDate2004-
heal.publisherInstitute of Information Theory and Automation of the ASCRen
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μαθηματικώνel
heal.typejournalArticle-
heal.type.elΆρθρο Περιοδικούel
heal.type.enJournal articleen

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