Estimating the spectral measure of an extreme value distribution

被引:37
作者
Einmahl, JHJ [1 ]
deHaan, L [1 ]
Sinha, AK [1 ]
机构
[1] ERASMUS UNIV ROTTERDAM,ROTTERDAM,NETHERLANDS
关键词
dependence structure; empirical process; estimation; functional central limit theorem; multivariate extremes; Vapnik-Cervonenkis (VC) class;
D O I
10.1016/S0304-4149(97)00065-3
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Let (X-1, Y-1), (X-2, Y-2),...,(X-n, Y-n) be a random sample from a bivariate distribution function F which is in the domain of attraction of a bivariate extreme value distribution function G. This G is characterized by the extreme value indices and its spectral measure or angular measure. The extreme value indices determine both the marginals and the spectral measure determines the dependence structure, In this paper, we construct an empirical measure, based on the sample, which is a consistent estimator of the spectral measure. We also show for positive extreme value indices the asymptotic normality of the estimator under a suitable 2nd order strengthening of the bivariate domain of attraction condition. (C) 1997 Elsevier Science B.V.
引用
收藏
页码:143 / 171
页数:29
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