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2008 A class of unbiased location invariant Hill-type estimators for heavy tailed distributions
Jiaona Li, Zuoxiang Peng, Saralees Nadarajah
Electron. J. Statist. 2: 829-847 (2008). DOI: 10.1214/08-EJS276

Abstract

Based on the methods provided in Caeiro and Gomes (2002) and Fraga Alves (2001), a new class of location invariant Hill-type estimators is derived in this paper. Its asymptotic distributional representation and asymptotic normality are presented, and the optimal choice of sample fraction by Mean Squared Error is also discussed for some special cases. Finally comparison studies are provided for some familiar models by Monte Carlo simulations.

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Jiaona Li. Zuoxiang Peng. Saralees Nadarajah. "A class of unbiased location invariant Hill-type estimators for heavy tailed distributions." Electron. J. Statist. 2 829 - 847, 2008. https://doi.org/10.1214/08-EJS276

Information

Published: 2008
First available in Project Euclid: 23 September 2008

zbMATH: 1320.62111
MathSciNet: MR2443198
Digital Object Identifier: 10.1214/08-EJS276

Subjects:
Primary: 62G32
Secondary: 65C05

Keywords: asymptotic normality , Location invariant Hill-type heavy tailed index estimator , second order regular variation

Rights: Copyright © 2008 The Institute of Mathematical Statistics and the Bernoulli Society

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