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Statistics
A Journal of Theoretical and Applied Statistics
Volume 56, 2022 - Issue 3
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Research Article

Location invariant heavy tail index estimation with block method

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Pages 479-497 | Received 08 Mar 2021, Accepted 22 Apr 2022, Published online: 10 May 2022
 

Abstract

Motivated by the work of Qi [On the tail index of a heavy tailed distribution. Ann Inst Stat Math. 2010;62:277–298] and Fraga Alves [A location invariant Hill-type estimator. Extremes. 2001b;4:199–217], a new class of location invariant Hill-type estimators for heavy tail index is proposed. The weak consistency of the estimator is studied, the asymptotic expansion and limit distribution of the estimator are derived under second-order regular varying conditions. Simulation studies are performed to compare the new estimator with closely related estimators.

AMS 2000 Subject Classifications:

Acknowledgments

The authors would like to thank the editor and the two referees for careful reading and comments which greatly improved the paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

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