Multivariate generalized Pareto distributions: Parametrizations, representations, and properties

JOURNAL OF MULTIVARIATE ANALYSIS

卷:165

Article

Rootzen, Holger^1,2  Segers, Johan³  Wadsworth, Jennifer L.⁴ 

[1] Chalmers Univ Technol, Math Sci, SE-41296 Gothenburg, Sweden

[2] Univ Gothenburg, SE-41296 Gothenburg, Sweden

[3] Catholic Univ Louvain, Inst Stat Biostat & Sci Actuarielles, Vole Roman Pays 20, B-1348 Louvain La Neuve, Belgium

[4] Univ Lancaster, Math & Stat, Fylde Coll, Lancaster, England

关键词: Exceedances;    Maxima;    Stable tail dependence function;    Tail copula;    Linear combination;   

DOI  :  10.1016/j.jmva.2017.12.003

来源: Elsevier

【 摘 要 】

Multivariate generalized Pareto distributions arise as the limit distributions of exceedances over multivariate thresholds of random vectors in the domain of attraction of a max stable distribution. These distributions can be parametrized and represented in a number of different ways. Moreover, generalized Pareto distributions enjoy a number of interesting stability properties. An overview of the main features of such distributions is given, expressed compactly in several parametrizations, giving the potential user of these distributions a convenient catalogue of ways to handle and work with generalized Pareto distributions. (C) 2017 Elsevier Inc. All rights reserved.

【 授权许可】

Free