Asymptotic properties of generalized DPR statistic

DOI10.1007/s10986-012-9158-4zbMath1322.62095OpenAlexW2001802275MaRDI QIDQ392996

Marijus Vaičiulis

Publication date: 15 January 2014

Published in: Lithuanian Mathematical Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10986-012-9158-4

zbMATH Keywords

asymptotic normalitytail indexPickands estimatorHill estimatormean-squared errorDPR estimator

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Central limit and other weak theorems (60F05) Statistics of extreme values; tail inference (62G32)

Related Items (4)

Location invariant heavy tail index estimation with block method ⋮ Inference of high quantiles of a heavy-tailed distribution from block data ⋮ An estimator of heavy tail index through the generalized jackknife methodology ⋮ A review of more than one hundred Pareto-tail index estimators

Cites Work

• Several modifications of DPR estimator of the tail index
• On the tail index of a heavy tailed distribution
• A moment estimator for the index of an extreme-value distribution
• Statistics of extremes for IID data and breakthroughs in the estimation of the extreme value index: Laurens de Haan leading contributions
• Statistical inference using extreme order statistics
• A simple general approach to inference about the tail of a distribution
• A new estimator for a tail index
• A class of asymptotically unbiased semi-parametric estimators of the tail index.
• A class of unbiased location invariant Hill-type estimators for heavy tailed distributions
• On the estimation of the parameters of multivariate stable distributions
• More on \(p\)-stable convex sets in Banach spaces
• Comparison of tail index estimators

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