A class of location invariant estimators for heavy tailed distributions

被引：0
|
作者：
Zhang, Lvyun [1 ]
Chen, Shouquan [1 ]
机构：
[1] Southwest Univ, Sch Math & Stat, Chongqing, Peoples R China
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2023年 / 52卷 / 03期
关键词：
Asymptotic normality; location invariant heavy tailed index estimator; second order regular variation; MOMENT ESTIMATOR; INDEX; HILL; INFERENCE; SUMS;
D O I：
10.1080/03610926.2021.1931335
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
In this paper, a new class of location-invariant semi-parametric estimators of a positive extreme value index gamma>0 is proposed. Its asymptotic distributional representation and asymptotic normality are derived, and the optimal choice of the 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.
引用
收藏
页码：896 / 917
页数：22
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