Nonparametric rank-based tests of bivariate extreme-value dependence

JOURNAL OF MULTIVARIATE ANALYSIS

卷:101

Article

Kojadinovic, Ivan^1,3  Yan, Jun² 

[1] Univ Pau & Pays Adour, Lab Math & Applicat, CNRS, UMR 5142, F-64013 Pau, France

[2] Univ Connecticut, Dept Stat, Storrs, CT 06269 USA

[3] Univ Auckland, Dept Stat, Auckland 1, New Zealand

关键词: Contiguity;    Extreme-value copulas;    Local power comparisons;    Multiplier central limit theorem;    Pseudo-observations;    Ranks;   

DOI  :  10.1016/j.jmva.2010.05.004

来源: Elsevier

【 摘 要 】

A new class of tests of extreme-value dependence for bivariate copulas is proposed. It is based on the process comparing the empirical copula with a natural nonparametric rank-based estimator of the unknown copula under extreme-value dependence. A multiplier technique is used to compute approximate p-values for several candidate test statistics. Extensive Monte Carlo experiments were carried out to compare the resulting procedures with the tests of extreme-value dependence recently studied in Ben Ghorbal et al. (2009) [1] and Kojadinovic and Van (2010) [19]. The finite-sample performance study of the tests is complemented by local power calculations. (c) 2010 Elsevier Inc. All rights reserved.

【 授权许可】

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