Goodness-of-fit tests for generalized logarithmic series distribution

被引:10
作者
Famoye, F [1 ]
机构
[1] Cent Michigan Univ, Dept Math, Mt Pleasant, MI 48859 USA
关键词
Monte Carlo simulation; bootstrap; empirical distribution function; power;
D O I
10.1016/S0167-9473(99)00048-1
中图分类号
TP39 [计算机的应用];
学科分类号
081203 [计算机应用技术]; 0835 [软件工程];
摘要
Goodness-of-fit test statistics based on the empirical distribution function (EDF) are considered for the generalized logarithmic series distribution. The a levels of the tests for small or moderate sample sizes are close to the chosen nominal 5% and 10% significance levels. For small or moderate sample sizes, the tests are compared with respect to their simulated power of detecting some alternative hypotheses against a null hypothesis of generalized logarithmic series distribution. The discrete version of the Cramer-von Mises and Anderson-Darling tests are found to be the most powerful pair among the EDF tests. (C) 2000 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:59 / 67
页数:9
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