一类上界型拟合优度检验统计量的精确分布

On Exact Distribution of a Class of Supremum-type\\Statistics for Goodness of Fit

  • 摘要: 对于简单假设的拟合优度检验, Zhang (2002)构造出一类上界型检验. 取不同的参数\lambda和不同的权函数q(t), 这类检验包含了Kolmogorov-Smirov检验, Berk and Jones (1979)检验等已有的上界型检验. 文献中仅对极少数\lambda和q(t)所对应的检验给出了零假设下的精确分布. 然而, 针对不同的问题, ``好''的检验是不同的, 因此有必要对任意给定的\lambda和q(t)情况, 讨论该类检验. 本文对任意给定的\lambda和q(t)\equiv 1情况, 导出了相应上界型检验统计量在零假设下的精确分布. 当样本容量n较大时, 精确分布的计算时间较长, 本文还通过模拟比较得到了在不同样本量下, 应采用的计算方法. 最后, 给出一个实际例子对前述方法加以简单说明.

     

    Abstract: For goodness of fit tests with simple null hypothesis, Zhang (2002) constructed a classes of supremum-type tests. Different parameter \lambda and different weighted function q(t) result in different tests, including the Kolmogorov-Smirov test, Berk and Jones (1979) test and so on. So far, only a few tests corresponding to particular \lambda and q(t) have been studied in the literature. However, for different problems, the ``best'' tests are different. It is necessary to discuss the tests for all \lambda and the general q(t). In this paper, the exact distributions of the test statistics for all \lambda and q(t)\equiv 1 are derived. When sample size n is large, it takes a long time to get the exact quantile. So we give some advice on the computation methods for different sample size by simulation studies, and a real example to simply illustrate the above methods.

     

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