Exact tail asymptotics in bivariate scale mixture models

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Serval ID
serval:BIB_A8E6D7A632C8
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Exact tail asymptotics in bivariate scale mixture models
Journal
Extremes
Author(s)
Hashorva E.
ISSN
1386-1999 (Print)
1572-915X (Electronic)
Publication state
Published
Issued date
2012
Peer-reviewed
Oui
Volume
15
Number
1
Pages
109-128
Language
english
Abstract
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.
Keywords
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
Yes
Create date
31/01/2011 13:20
Last modification date
01/10/2019 7:19
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