GOODNESS-OF-FIT TESTS FOR THE BETA GOMPERTZ DISTRIBUTION

被引：2

作者：

Abu-Zinadah, Hanaa ^{[1
]}

Binkhamis, Asmaa ^{[1
]}

机构：

[1] Univ Jeddah, Dept Stat, Coll Sci, Jeddah, Saudi Arabia

来源：

THERMAL SCIENCE | 2020年 / 24卷

关键词：

Beta Gompertz distribution; Monte Carlo simulation; goodness-of-fit test; complete sampling;

D O I：

10.2298/TSCI20S1069A

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

This article studied the goodness-of-fit tests for the beta Gompertz distribution with four parameters based on a complete sample. The parameters were estimated by the maximum likelihood method. Critical values were found by Monte Carlo simulation for the modified Kolmogorov-Smirnov, Anderson-Darling, Cramer-von Mises, and Lilliefors test statistics. The power of these test statistics founded the optimal alternative distribution. Real data applications were used as examples for the goodness of fit tests.

引用

页码：S69 / S81

页数：13

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