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Subsampling Extremes: From Block Maxima to Smooth Tail Estimation

Journal of Multivariate Analysis (J. Multivar. Anal.), 2012
2 April 2012
Stefan Wager
ArXiv (abs)PDFHTML
Abstract

We study a new estimator for the tail index of a distribution in the Frechet domain of attraction that arises naturally by computing subsample maxima. This estimator is equivalent to taking a U-statistic over a Hill estimator with two order statistics. The estimator presents multiple advantages over the Hill estimator. In particular, it has asymptotically smooth sample paths as a function of the threshold k, making it considerably more stable than the Hill estimator. The estimator also admits a simple and intuitive threshold selection rule that does not require fitting a second-order model.

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