Minimum distance estimators in extreme value distributions

被引：5

作者：

Dietrich, D ^{[1
]}

Husler, J ^{[1
]}

机构：

[1] UNIV BERN,DEPT MATH STAT,CH-3012 BERN,SWITZERLAND

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 1996年 / 25卷 / 04期

关键词：

extreme value distribution; Gumbel distribution; minimum distance; maximum likelihood estimator; censored samples; efficiency; robustness;

D O I：

10.1080/03610929608831725

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：

We define minimum distance estimators for the parameters of the extreme value distribution G(0) based on the Cramer-von-Mises distance. These estimators are rather robust and consistent, but asymptotically less efficient than the maximum likelihood estimators which are not robust. A small simulation study for finite sample size show that under G(0) the finite efficiency of the minimum distance estimators is rather similar to the maximum likelihood ones.

引用

页码：695 / 703

页数：9

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