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dc.contributor.authorZografos, K.en
dc.date.accessioned2015-11-24T17:24:00Z-
dc.date.available2015-11-24T17:24:00Z-
dc.identifier.issn0020-3157-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/12831-
dc.rightsDefault Licence-
dc.subjectf-dissimilarityen
dc.subjectf-dissimilarity statisticen
dc.subjectasymptotic distributionen
dc.subjectmultinomial distributionen
dc.subjectmultivariate normal distributionen
dc.subjecttesting statistical hypothesesen
dc.subjectdivergence statisticsen
dc.subjectmultinomial goodnessen
dc.subjectpopulationsen
dc.subjectdiversityen
dc.subjectfiten
dc.titlef-dissimilarity of several distributions in testing statistical hypothesesen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primaryDoi 10.1023/A:1003443215838-
heal.identifier.secondary<Go to ISI>://000074666200006-
heal.identifier.secondaryhttp://link.springer.com/content/pdf/10.1023%2FA%3A1003443215838.pdf-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μαθηματικώνel
heal.publicationDate1998-
heal.abstractVarious problems in statistics have been treated by the decision rule, based on the concept of distance between distributions. The aim of this paper is to give an approach for testing statistical hypotheses, using a general class of dissimilarity measures among k greater than or equal to 2 distributions. The test statistics are obtained by the replacement, in the expression of the dissimilarity measure, of the unknown parameters by their maximum likelihood estimators. The asymptotic distributions of the resulting test statistics are investigated and the results are applied to multinomial and multivariate normal populations.en
heal.publisherSpringer Verlag (Germany)en
heal.journalNameAnnals of the Institute of Statistical Mathematicsen
heal.journalTypepeer reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά). ΜΑΘ

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