Confidence regions for high quantiles of a heavy tailed distribution

被引：25

作者：

Peng, Liang ^{[1
]}

Qi, Yongcheng

机构：

[1] Georgia Inst Technol, Sch Math, Atlanta, GA 30332 USA

[2] Univ Minnesota, Dept Math & Stat, Duluth, MN 55812 USA

来源：

ANNALS OF STATISTICS | 2006年 / 34卷 / 04期

关键词：

confidence region; data tilting; empirical likelihood method; heavy tail; high quantile;

D O I：

10.1214/009053606000000416

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：

Estimating high quantiles plays an important role in the context of risk management. This involves extrapolation of an unknown distribution function. In this paper we propose three methods, namely, the normal approximation method, the likelihood ratio method and the data tilting method, to construct confidence regions for high quantiles of a heavy tailed distribution. A simulation study prefers the data tilting method.

引用

页码：1964 / 1986

页数：23

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