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首页> 外文期刊>Open Journal of Statistics >On the Power Performance of Test Statistics for the Generalized Rayleigh Interval Grouped Data
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On the Power Performance of Test Statistics for the Generalized Rayleigh Interval Grouped Data

机译:广义瑞利区间分组数据检验统计量的幂性能

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摘要

In this paper, the weighted Kolmogrov-Smirnov, Cramer von-Miss and the Anderson Darling test statistics are considered as goodness of fit tests for the generalized Rayleigh interval grouped data. An extensive simulation process is conducted to evaluate their controlling of type 1 error and their power functions. Generally, the weighted Kolmogrov-Smirnov test statistics show a relatively better performance than both, the Cramer von-Miss and the Anderson Darling test statistics. For large sample values, the Anderson Darling test statistics cannot control type 1 error but for relatively small sample values it indicates a better performance than the Cramer von-Miss test statistics. Best selection of the test statistics and highlights for future studies are also explored.
机译:在本文中,加权的Kolmogrov-Smirnov,Cramer von-Miss和Anderson Darling检验统计量被认为是广义Rayleigh区间分组数据的拟合检验的优良性。进行了广泛的仿真过程以评估其对1型误差的控制及其功率函数。通常,加权的Kolmogrov-Smirnov检验统计数据显示的性能要比Cramer von-Miss和Anderson Darling检验统计数据都更好。对于较大的样本值,Anderson Darling测试统计数据无法控制1类错误,但是对于较小的样本值,它表示比Cramer von-Miss测试统计数据更好的性能。还探讨了测试统计数据的最佳选择和未来研究的重点。

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