ABSTRACT The Rayleigh distribution is widely used to model right skewed data and therefore it is important to develop efficient goodness of fit tests for this distribution. In this article, we introduce some new test statistics for examining the Rayleigh goodness of fit based on correcting moments of nonparametric probability density functions of entropy estimators. Critical points and power of the tests are explored by simulation. We show that the proposed tests are more powerful than competitor tests. Finally, the proposed tests are illustrated by a real data example.

中文翻译：

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熵估计器的非参数概率密度函数用于检验瑞利分布

摘要 Rayleigh 分布广泛用于对右偏数据建模，因此为该分布开发有效的拟合优度检验非常重要。在本文中，我们介绍了一些新的检验统计量，用于检查基于熵估计器的非参数概率密度函数的校正矩的 Rayleigh 拟合优度。通过模拟探索测试的关键点和能力。我们表明，提议的测试比竞争对手的测试更强大。最后，通过一个真实的数据示例说明了所提出的测试。