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Asymptotically Unbiased Estimation of the Coefficient of Tail Dependence
Authors:YURI GOEGEBEUR  ARMELLE GUILLOU
Affiliation:1. Department of Mathematics and Computer Science, University of Southern Denmark;2. Institut Recherche Mathématique Avancée, Université de Strasbourg et CNRS
Abstract:Abstract. We introduce and study a class of weighted functional estimators for the coefficient of tail dependence in bivariate extreme value statistics. Asymptotic normality of these estimators is established under a second‐order condition on the joint tail behaviour, some conditions on the weight function and for appropriately chosen sequences of intermediate order statistics. Asymptotically unbiased estimators are constructed by judiciously chosen linear combinations of weighted functional estimators, and variance optimality within this class of asymptotically unbiased estimators is discussed. The finite sample performance of some specific examples from our class of estimators and some alternatives from the recent literature are evaluated with a small simulation experiment.
Keywords:bias‐correction  coefficient of tail dependence  multivariate extremes  second‐order condition
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