Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/882
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dc.contributor.authorMladenović, Pavleen_US
dc.date.accessioned2022-08-15T18:08:22Z-
dc.date.available2022-08-15T18:08:22Z-
dc.date.issued2005-01-01-
dc.identifier.issn0040585Xen
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/882-
dc.description.abstractLet (k n ) be a sequence of positive integers such that k n → ∞ as n → ∞. Let X n1 *,..., X nkn , n ∈ N, be a double array of random variables such that for each n the random variables X n1 *,..., X nkn * are independent with a common distribution function F n , and let us denote M n * = max{X n1 *,..., X nkn *}. We consider an example of double array random variables connected with a certain combinatorial waiting time problem (including both dependent and independent cases), where k n = n for all n and the limiting distribution function for M n * is Λ(X) = exp(-e -x ), although none of the distribution functions Fn belongs to the domain of attraction D(Λ). We also generalize the Mejzler-de Haan theorem and give the necessary and sufficient conditions for the sequence (F n ) under which there exist sequences a n > 0 and b n ∈ R, n ∈ N, such that F nkn (a n x+b n ) → exp(-e -x ) as n → ∞ for every real x.en
dc.relation.ispartofTheory of Probability and its Applicationsen
dc.subjectDomain of attractionen
dc.subjectDouble arrayen
dc.subjectDouble exponential distributionen
dc.subjectExtreme value distributionsen
dc.subjectRegular variationen
dc.titleA generalization of the Mejzler-de Haan theoremen_US
dc.typeArticleen_US
dc.identifier.doi10.1137/S0040585X97981561-
dc.identifier.scopus2-s2.0-33646045873-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/33646045873-
dc.contributor.affiliationProbability and Mathematical Statisticsen_US
dc.relation.firstpage141en
dc.relation.lastpage153en
dc.relation.volume50en
dc.relation.issue1en
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.deptProbability and Mathematical Statistics-
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