Dense classes of multivariate extreme value distributions

被引：17
|
作者：
Fougeres, Anne-Laure [1 ]
Mercadier, Cecile [1 ]
Nolan, John P. [2 ]
机构：
[1] Univ Lyon 1, CNRS, Inst Camille Jordan, F-69622 Villeurbanne, France
[2] American Univ, Dept Math Stat, Washington, DC 20016 USA
来源：
JOURNAL OF MULTIVARIATE ANALYSIS | 2013年 / 116卷
关键词：
Multivariate extreme value distribution; Extremal dependence; Max-stable; Dependence function; Logistic distributions; Models for multivariate extremes; TAIL DEPENDENCE; ESTIMATOR; MODELS;
D O I：
10.1016/j.jmva.2012.11.015
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 this paper, we explore tail dependence modeling in multivariate extreme value distributions. The measure of dependence chosen is the scale function, which allows combinations of distributions in a very flexible way. The correspondences between the scale function and the spectral measure or the stable tail dependence function are given. Combining scale functions by simple operations, three parametric classes of laws are (re)constructed and analyzed, and resulting nested and structured models are discussed. Finally, the denseness of each of these classes is shown. (C) 2012 Elsevier Inc. All rights reserved.
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页码：109 / 129
页数：21
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