This talk has been automatically captioned. You can remove these by pressing CC on the video toolbar.

Name: Jonathan El Methni

Talk Title: A bias-reduced version of the Weissman extreme quantile estimator

Abstract: Weissman extrapolation device for estimating extreme quantiles is based on two estimators: an order statistic to estimate an intermediate quantile and an estimator of the tail index.  The common practice is to select the same intermediate sequence for both estimators. In this work, we show how an adaptated choice of two different  intermediate sequences leads to a reduction of the asymptotic bias associated with the resulting Weissman estimator.  Our approach is compared to other bias reduced estimators of extreme quantiles both on simulated and real data.

This is a joint work with Stéphane Girard (Inria France)

This talk is a contributed talk at EVA 2021.