Please use this identifier to cite or link to this item: https://olympias.lib.uoi.gr/jspui/handle/123456789/13470
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dc.contributor.authorMenendez, M. L.en
dc.contributor.authorPardo, L.en
dc.contributor.authorTsairidis, C.en
dc.contributor.authorZografos, K.en
dc.date.accessioned2015-11-24T17:27:55Z-
dc.date.available2015-11-24T17:27:55Z-
dc.identifier.issn0026-1335-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/13470-
dc.rightsDefault Licence-
dc.subjectdivergenceen
dc.subjectentropyen
dc.subjectexponential familyen
dc.subjectmahalanobis distanceen
dc.subjectmultivariate normal distributionen
dc.subjectordering populationsen
dc.subjectselection of populationsen
dc.subjectsubset selection approachen
dc.subjectdivergenceen
dc.subjectentropyen
dc.titleSelection of the best population: an information theoretic approachen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primaryDOI 10.1007/s001840200232-
heal.identifier.secondary<Go to ISI>://000185844000002-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μαθηματικώνel
heal.publicationDate2003-
heal.abstractThis paper is devoted to the statistical problem of ranking and selection populations by using the subset selection formulation. The interest is focused (i) on the selection of the best population among k independent populations and (ii) on the selection of the best population, which is closest to an additional standard or control population. With respect to the first problem the populations are ranked in terms of entropies of their distributions and the population whose distribution has maximum entropy is selected. For the second problem the populations are ranked in terms of divergences between their distributions and the distribution of the standard or control population and the population with the minimum divergence is selected. In each case the populations are assumed to have general parametric densities satisfying the classical regularity conditions of asymptotic statistic. Large sample properties of the estimators of entropies and divergences of the populations will be studied and used in order to determine the probabilities of correct selection of the proposed asymptotic selection rules. Illustrative examples, including a numerical example using real medical data appeared-in the literature; will be given for multivariate homoscedastic normal populations and populations described by the regular exponential family of distributions.en
heal.publisherSpringer Verlag (Germany)en
heal.journalNameMetrikaen
heal.journalTypepeer reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά). ΜΑΘ

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