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Estimation of bivariate excess probabilities for elliptical models
Abdous B. et al
http://hal.archives-ouvertes.fr/hal-00117001
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Mathematics/Statistics
Estimation of bivariate excess probabilities for elliptical models
Belkacem Abdous () 1, Anne-Laure Fougères () 2, Kilani Ghoudi () 3, Philippe Soulier () 2
1:  Département de médecine sociale et préventive (DMPS)
http://w3.fmed.ulaval.ca/dmsp/accueil/
Université Laval
Département de Médecine sociale et préventive Faculté de Médecine 2180 Chemin Sainte-Foy Pavillon de l'Est, bureau 1108 Université Laval Québec (Québec), Canada, G1K 7P4
Canada
2:  Modélisation aléatoire de Paris X (MODAL'X)
http://www.u-paris10.fr/MODALX/0/fiche___laboratoire/
Université Paris X - Paris Ouest Nanterre La Défense
France
3:  College of Business and Economics Statistics Department (CBE STAT)
http://www.cbe.uaeu.ac.ae/Academics/Departments/stat/index.htm
United Arab Emirates University
College of Business & Economics, UAE University, POB 17555
United Arab Emirates
Let $(X,Y)$ be a random vector whose conditional excess probability $ \theta(x,y) := P(Y \leq y ~ | \; X >x)$ is of interest. Estimating this kind of probability is a delicate problem as soon as $x$ tends to be large, since the conditioning event becomes an extreme set. Assume that $(X,Y)$ is elliptically distributed, with a rapidly varying radial component. In this paper, three statistical procedures are proposed to estimate $\theta(x,y)$, for fixed $x,y$, with $x$ large. They respectively make use of an approximation result of Abdous {\it et al.} (cf. \citet[Theorem 1]{AFG05}), a new second-order refinement of Abdous {\it et al.}'s Theorem 1, and a non-approximating method. The estimation of the conditional quantile function $\theta(x, \cdot)^\leftarrow$ for large fixed $x$ is also addressed, and these methods are compared via simulations.
English

Conditional excess probability – asymptotic independence – elliptic law.
AMS 62G32, 60G70

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TEX
elsart.cls(55.1 KB)
kotz-1-theta.eps(20 KB)
kotz-4-theta.eps(20 KB)
lognormal-theta.eps(19.7 KB)
norm-theta.eps(19.3 KB)
quantile.eps(18.4 KB)
afgsrev.tex(65.8 KB)
PS
afgsrev.ps(312.7 KB)
PDF
afgsrev.pdf(306.8 KB)