Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/37243

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dc.contributor.authorFerreira, Marta Susanapor
dc.contributor.authorSilva, Sérgiopor
dc.date.accessioned2015-09-15T11:50:00Z-
dc.date.available2015-09-15T11:50:00Z-
dc.date.issued2014-
dc.identifier.issn1687-952Xpor
dc.identifier.urihttps://hdl.handle.net/1822/37243-
dc.description.abstractMeasuring tail dependence is an important issue in many applied sciences in order to quantify the risk of simultaneous extreme events. A usual measure is given by the tail dependence coefficient. The characteristics of events behave quite differently as these become more extreme, whereas we are in the class of asymptotic dependence or in the class of asymptotic independence. The literature has emphasized the asymptotic dependent class but wrongly infers that tail dependence will result in the overestimation of extreme value dependence and consequently of the risk. In this paper we analyze this issue through simulation based on a heuristic procedure.por
dc.description.sponsorshipThis research was financed by FEDER Funds through "Programa Operacional Factores de Competitividade - COMPETE" and Portuguese Funds through FCT - "Fundação para a Ciência e a Tecnologia", within the Project PEst-OE/MAT/UI0013/2014por
dc.language.isoengpor
dc.publisherHindawi Publishing Corporationpor
dc.relationPEst-OE/MAT/UI0013/2014por
dc.rightsopenAccesspor
dc.subjectTail dependencepor
dc.subjectasymptotic independencepor
dc.subjectextreme value theorypor
dc.titleAn analysis of a heuristic procedure to evaluate tail (in)dependencepor
dc.typearticlepor
dc.peerreviewedyespor
dc.relation.publisherversionhttp://www.hindawi.com/journals/jps/2014/913621/por
sdum.publicationstatuspublishedpor
oaire.citationTitleJournal of Probability and Statisticspor
oaire.citationVolume2014por
dc.identifier.doi10.1155/2014/913621por
dc.subject.fosCiências Naturais::Matemáticaspor
dc.subject.wosScience & Technologypor
sdum.journalJournal of Probability and Statisticspor
Aparece nas coleções:CMAT - Artigos em revistas com arbitragem / Papers in peer review journals

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