Nonparametric rank-based tests of bivariate extreme-value dependence

Ivan Kojadinovic (1) , J. Yan (2)

1 LMAP - Laboratoire de Mathématiques et de leurs Applications [Pau]
2 Center for Human Genetics, University of Leuven School of Medicine

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 Yan (2010) [19]. The finite-sample performance study of the tests is complemented by local power calculations. © 2010 Elsevier Inc.

Domaines: Probabilités [math.PR]

Ivan Kojadinovic, J. Yan. Nonparametric rank-based tests of bivariate extreme-value dependence. Journal of Multivariate Analysis, 2010, 101 (9), pp.2234-2249. ⟨10.1016/j.jmva.2010.05.004⟩. ⟨hal-00865062⟩