Subsampling Extremes: From Block Maxima to Smooth Tail Estimation

Stefan Wager

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arXiv · 1204.0316

Subsampling Extremes: From Block Maxima to Smooth Tail Estimation

Stefan Wager

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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. Journal of Multivariate Analysis, 130, 2014

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Stefan Wager. 2012-04-02. Subsampling Extremes: From Block Maxima to Smooth Tail Estimation. https://arxiv.org/abs/1204.0316

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