Goodness-of-fit test for the Birnbaum-Saunders distribution based on the Kullback-Leibler information

被引：0

作者：

Mendonca, Ednario ^{[1
]}

Barros, Michelli ^{[2
]}

Campos, Joelson ^{[2
]}

机构：

[1] Univ Estadual Paraiba, Dept Estat, Campina Grande, Brazil

[2] Univ Fed Campina Grande, Dept Estat, Campina Grande, Brazil

来源：

CHILEAN JOURNAL OF STATISTICS | 2019年 / 10卷 / 01期

关键词：

Anderson-Darling and Cramer-von Mises tests; Information measures; Maximum likelihood estimation; Monte Carlo method; Power test; R software; REGRESSION-MODELS; CHANGE-POINT; VERSION; SHAPE;

D O I：

暂无

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：

In this work, we propose a goodness-of-fit test based on the Kullback-Leibler information for the Birnbaum-Saunders distribution. We use Monte Carlo simulations to evaluate the size and power of the proposed test for several alternative hypotheses under different sample sizes. We compare the powers with standard goodness-of-fit tests based as the Anderson-Darling and Cramer-von Mises tests. Finally, we illustrate the proposed test with a real data set to show its potential applications.

引用

页码：41 / 53

页数：13

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