Moment estimators of the extreme value index for randomly censored data in the Weibull domain of attraction
Abstract
This paper addresses the problem of estimating the extreme value index in presence of random censoring for distributions in the Weibull domain of attraction. The methodologies introduced in [Worms 2014], in the heavytailed case, are adapted here to the negative extreme value index framework, leading to weighted versions of the popular moments of relative excesses. This leads to the de nition of two families of estimators (with an adaptation of the so called Moment estimator as a particular case), for which the consistency is proved under a rst order condition. Illustration of their performance, coming from an extensive simulation study, are provided.
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