Extremal attractors of Liouville copulas

JOURNAL OF MULTIVARIATE ANALYSIS

卷:160

Article

Belzile, Leo R.¹  Neglehova, Johanna G.² 

[1] EPFL SB MATH STAT, Stn 8, CH-1015 Lausanne, Switzerland

[2] McGill Univ, Dept Math & Stat, 805 Rue Sherbrooke Ouest, Montreal, PQ H3A 0B9, Canada

关键词: Extremal attractor;    Extremal function;    de Haan decomposition;    Liouville copula;    Scaled extremal Dirichlet model;    Stable tail dependence function;   

DOI  :  10.1016/j.jmva.2017.05.008

来源: Elsevier

【 摘 要 】

Liouville copulas introduced in McNeil and Ne lehova (2010) are asymmetric generalizations of the ubiquitous Archimedean copula class. They are the dependence structures of scale mixtures of Dirichlet distributions, also called Liouville distributions. In this paper, the limiting extreme-value attractors of Liouville copulas and of their survival counterparts are derived. The limiting max-stable models, termed here the scaled exfremal Dirichlet, are new and encompass several existing classes of multivariate max-stable distributions, including the logistic, negative logistic and extremal Dirichlet. As shown herein, the stable tail dependence function and angular density of the scaled extremal Dirichlet model have a tractable form, which in turn leads to a simple de Haan representation. The latter is used to design efficient algorithms for unconditional simulation based on the work of Dombry et al. (2016) and to derive tractable formulas for maximum-likelihood inference. The scaled extremal Dirichlet model is illustrated on river flow data of the river Isar in southern Germany. (C) 2017 Elsevier Inc. All rights reserved.

【 授权许可】

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