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Nonparametric probability density functions of entropy estimators applied to testing the Rayleigh distribution

机译:应用于测试瑞利分布的熵估计器的非参数概率密度函数

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摘要

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.
机译:瑞利分布广泛用于建模正确的偏斜数据,因此为此分布提供高效的拟合测试。在本文中,我们基于熵估计器的非参数概率密度函数的校正力矩,介绍了一些新的测试统计信息,用于检查尺寸适合的尺寸适合。通过模拟探讨了测试的关键点和力量。我们表明,拟议的测试比竞争对手测试更强大。最后,所提出的测试由真实的数据示例说明。

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