Estimation of the extreme value index in a censorship framework: Asymptotic and finite sample behavior

We revisit the estimation of the extreme value index for randomly censored data from a heavy tailed distribution. We introduce a new class of estimators which encompasses earlier proposals given in Worms and Worms (2014) and Beirlant et al. (2018), which were shown to have good bias properties compa...

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Veröffentlicht in:	Journal of statistical planning and inference 2019, Vol.202, p.31-56
Hauptverfasser:	Beirlant, Jan, Worms, Julien, Worms, Rym
Format:	Artikel
Sprache:	eng
Schlagworte:	Mathematics Statistics
Online-Zugang:	Volltext
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