Location invariant heavy tail index estimation with block method

被引：1

作者：

Hu, Shuang ^{[1
]}

Peng, Zuoxiang ^{[1
]}

Nadarajah, Saralees ^{[2
]}

机构：

[1] Southwest Univ, Sch Math & Stat, Chongqing, Peoples R China

[2] Univ Manchester, Dept Math, Manchester, Lancs, England

来源：

STATISTICS | 2022年 / 56卷 / 03期

关键词：

Asymptotic normality; consistency; Hill-type estimator; Primary; Secondary; HILL;

D O I：

10.1080/02331888.2022.2071898

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：

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.

引用

页码：479 / 497

页数：19