A Goodness-of-Fit Test for the Gumbel Distribution Based on Kullback-Leibler Information

被引：18

作者：

Perez-Rodriguez, Paulino ^{[1
]}

Vaquera-Huerta, Humberto ^{[1
]}

Villasenor-Alva, Jose A. ^{[1
]}

机构：

[1] Colegio Postgrad, Programa Estadist, Montecillo 56230, Mexico

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2009年 / 38卷 / 06期

关键词：

Entropy; Monte Carlo simulation; Test power; EXTREME-VALUE DISTRIBUTION;

D O I：

10.1080/03610920802316658

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：

A goodness-of-fit test for the Gumbel distribution is proposed. This test is based on the Kullback-Leibler discrimination information methodology proposed by Song (2002). The critical values of the test were obtained by using Monte Carlo simulation for small sample sizes and different levels of significance. The proposed test is compared with the tests developed by Stephens (1977), Chandra et al. (1981), and the test given by Kinnison (1989) in terms of their power by considering various alternative distributions. Simulation results show that the Kullback-Leibler information test has higher power than some of the studied tests.

引用

页码：842 / 855

页数：14

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