Estimating the conditional extreme-value index under random right-censoring

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Abstract

In extreme value theory, the extreme-value index is a parameter that controls the behavior of a cumulative distribution function in its right tail. Estimating this parameter is thus the first step when tackling a number of problems related to extreme events. In this paper, we introduce an estimator of the extreme-value index in the presence of a random covariate when the response variable is right-censored, whether its conditional distribution belongs to the Fréchet, Weibull or Gumbel domain of attraction. The pointwise weak consistency and asymptotic normality of the proposed estimator are established. Some illustrations on simulations are provided and we showcase the estimator on a real set of medical data.

AMS 2010 subject classifications

62G05
62G20
62G30
62G32
62N01
62N02

Keywords

Extreme-value index
Random covariate
Random right-censoring
Consistency
Asymptotic normality

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