Ratio of generalized Hill's estimator and its asymptotic normality theory

DOI10.3103/S1066530709020021zbMath1231.62091WikidataQ59245379 ScholiaQ59245379MaRDI QIDQ734562

Aliou Diop, Gane Samb Lo

Publication date: 13 October 2009

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

zbMATH Keywords

order statisticsextreme value theoryBrownian bridgesmaximum domain of attractionempirical and quantile processes

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Order statistics; empirical distribution functions (62G30) Statistics of extreme values; tail inference (62G32) Inference from stochastic processes (62M99)

Related Items (1)

A supermartingale argument for characterizing the functional Hill process weak law for small parameters

Cites Work

• A moment estimator for the index of an extreme-value distribution
• Kernel estimates of the tail index of a distribution
• Weighted empirical and quantile processes
• Estimating tails of probability distributions
• A note on the asymptotic normality of sums of extreme values
• Laws of large numbers for sums of extreme values
• A simple general approach to inference about the tail of a distribution
• Central limit theorems for sums of extreme values
• Asymptotic behavior of Hill's estimate and applications
• Statistics of Extremes
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