Gaussian approximation to the extreme value index estimator of a heavy-tailed distribution under random censoring

DOI10.3103/S106653071504002XzbMath1334.60090arXiv1302.1666OpenAlexW2963601974MaRDI QIDQ259855

Djamel Meraghni, Brahim Brahimi, Abdelhakim Necir

Publication date: 18 March 2016

Published in: Mathematical Methods of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1302.1666

zbMATH Keywords

random censoringempirical processHill estimatorextreme value indexGaussian approximation

Mathematics Subject Classification ID

Gaussian processes (60G15) Order statistics; empirical distribution functions (62G30) Extreme value theory; extremal stochastic processes (60G70) Statistics of extreme values; tail inference (62G32) Functional limit theorems; invariance principles (60F17)

Related Items (9)

Nonparametric estimation of the conditional tail index and extreme quantiles under random censoring ⋮ Bayesian estimation of the tail index of a heavy tailed distribution under random censoring ⋮ On the study of extremes with dependent random right-censoring ⋮ Nonparametric estimation of the conditional extreme-value index with random covariates and censoring ⋮ Penalized bias reduction in extreme value estimation for censored Pareto-type data, and long-tailed insurance applications ⋮ Estimation of extremes for Weibull-tail distributions in the presence of random censoring ⋮ On a relationship between randomly and non-randomly thresholded empirical average excesses for heavy tails ⋮ Estimation of the extreme value index in a censorship framework: asymptotic and finite sample behavior ⋮ Estimation of extremes for heavy-tailed and light-tailed distributions in the presence of random censoring

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