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arXiv · 1701.05458

Extreme value statistics for censored data with heavy tails under competing risks

Julien Worms·Rym Worms
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Abstract

This paper addresses the problem of estimating, in the presence of random censoring as well as competing risks, the extreme value index of the (sub)-distribution function associated to one particular cause, in the heavy-tail case. Asymptotic normality of the proposed estimator (which has the form of an Aalen-Johansen integral, and is the first estimator proposed in this context) is established. A small simulation study exhibits its performances for finite samples. Estimation of extreme quantiles of the cumulative incidence function is also addressed.

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Julien Worms, Rym Worms. 2017-01-19. Extreme value statistics for censored data with heavy tails under competing risks. https://arxiv.org/abs/1701.05458

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