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Functional Kernel Estimators of Conditional Extreme Quantiles

  • Laurent Gardes
  • Stèphane Girard
Conference paper
Part of the Contributions to Statistics book series (CONTRIB.STAT.)

Abstract

We address the estimation of “extreme” conditional quantiles i.e. when their order converges to one as the sample size increases. Conditions on the rate of convergence of their order to one are provided to obtain asymptotically Gaussian distributed kernel estimators. A Weissman-type estimator and kernel estimators of the conditional tail-index are derived, permitting to estimate extreme conditional quantiles of arbitrary order.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.INRIA Rhône-Alpes and LJKSaint-ImierFrance

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