Heavy tail index estimation based on block order statistics

被引：4

作者：

Xiong, Li ^{[1
]}

Peng, Zuoxiang ^{[1
]}

机构：

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

来源：

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION | 2020年 / 90卷 / 12期

关键词：

Asymptotic expansion; asymptotic normality; consistency; heavy tail index; INFERENCE;

D O I：

10.1080/00949655.2020.1769622

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A new kind of heavy tail index estimator is proposed by using block order statistics in this paper. The weak consistency of the estimator is derived. The asymptotic expansion and asymptotic normality of the estimator are considered under second order regular variation conditions. Small sample simulations are presented in terms of average mean and average mean squared error to support our findings by comparison with two known heavy tail estimators established by block order statistics method.

引用

页码：2198 / 2208

页数：11

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