Exact tail asymptotics in bivariate scale mixture models

Détails

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ID Serval
serval:BIB_A8E6D7A632C8
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Exact tail asymptotics in bivariate scale mixture models
Périodique
Extremes
Auteur⸱e⸱s
Hashorva E.
ISSN
1386-1999 (Print)
1572-915X (Electronic)
Statut éditorial
Publié
Date de publication
2012
Peer-reviewed
Oui
Volume
15
Numéro
1
Pages
109-128
Langue
anglais
Résumé
Let (X, Y) = (RU (1), RU (2)) be a given bivariate scale mixture random vector, with R > 0 independent of the bivariate random vector (U (1), U (2)). In this paper we derive exact asymptotic expansions of the joint survivor probability of (X, Y) assuming that R has distribution function in the Gumbel max-domain of attraction, and (U (1), U (2)) has a specific local asymptotic behaviour around some absorbing point. We apply our results to investigate the asymptotic behaviour of joint conditional excess distribution and the asymptotic independence for two models of bivariate scale mixture distributions.
Mots-clé
Tail asymptotics, Conditional excess distributions, Gumbel max-domain of attraction, Elliptically symmetric distributions, Dirichlet distributions, Residual tail dependence index, Davis-Resnick tail property
Web of science
Open Access
Oui
Création de la notice
31/01/2011 13:20
Dernière modification de la notice
14/02/2022 8:56
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