Asymptotically Unbiased Estimation of the Coefficient of Tail Dependence

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 an...

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Veröffentlicht in:Scandinavian journal of statistics 2013-03, Vol.40 (1), p.174-189
Hauptverfasser: GOEGEBEUR, YURI, GUILLOU, ARMELLE
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GUILLOU, ARMELLE
description 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.
doi_str_mv 10.1111/j.1467-9469.2012.00800.x
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subjects Asymptotic properties
bias-correction
coefficient of tail dependence
Distribution functions
Estimating techniques
Estimation bias
Estimators
Mathematics
Maximum likelihood estimation
multivariate extremes
Sampling bias
second-order condition
Simulations
Statism
Statistical estimation
Statistical methods
Statistical variance
Statistics
Studies
title Asymptotically Unbiased Estimation of the Coefficient of Tail Dependence
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