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Journal Articles Metrika Year : 2018

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

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 fi rst estimator proposed in this context) is established. A small simulation study exhibits its performances for fi nite samples. Estimation of extreme quantiles of the cumulative incidence function is also addressed.
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Dates and versions

hal-01418370 , version 1 (20-12-2016)
hal-01418370 , version 2 (13-01-2017)

Identifiers

Cite

Julien Worms, Rym Worms. Extreme value statistics for censored data with heavy tails under competing risks. Metrika, 2018, 81 (7), pp.849-889. ⟨10.1007/s00184-018-0662-3⟩. ⟨hal-01418370v2⟩
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