Bivariate tall estimation: dependence in asymptotic independence

被引:95
|
作者
Draisma, G
Drees, H
Ferreira, A
De Haan, L
机构
[1] Erasmus Univ, Med Ctr, Dept Publ Hlth, NL-3000 DR Rotterdam, Netherlands
[2] Univ Hamburg, Dept Math, D-20146 Hamburg, Germany
[3] EURANDOM, Eindhoven, Netherlands
[4] Univ Tecn Lisboa, ISA, P-1349017 Lisbon, Portugal
[5] Erasmus Univ, Inst Econometr, NL-3000 DR Rotterdam, Netherlands
关键词
asymptotic normality; bivariate extreme value distribution; coefficient of tail dependence; copula; failure probability; Hill estimator; moment estimator;
D O I
10.3150/bj/1082380219
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
In the classical setting of bivariate extreme value theory, the procedures for estimating the probability of an extreme event are not applicable if the componentwise maxima of the observations are asymptotically independent. To cope with this problem, Ledford and Tawn proposed a submodel in which the penultimate dependence is characterized by an additional parameter. We discuss the asymptotic properties of two estimators for this parameter in an extended model. Moreover, we develop an estimator for the probability of an extreme event that works in the case of asymptotic independence as well as in the case of asymptotic dependence, and prove its consistency.
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页码:251 / 280
页数:30
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