关于拟合优度检验的EDF统计量的若干评注(英语)

拟合优度检验是建立统计模型的一个重要手段,很多检验统计量用一个理想样本能达到它们自己的极值,但EDF统计量做不到,这无疑会影响检验的势。在本文中,我们将提出某些调整型EDF统计量,它们具有这些性质,并改进了EDF检验,蒙得卡罗模拟表明,调整型EDF统计量在很多场合要必EDF具有更高的势,特别对重尾的备选分布更是这样,我们还考察了检验的形态与它们的极值点之间的关系。

Some Comments on the EDF Statistics of Goodness-of-Fit Tests

The test of goodness-of-fit is an important means to establish a statistical model. Many test statistics reach their own extreme value at an "ideal sample" but EDF statistics not. It certainly affects the power of the tests. In present paper, we propose some adjusted EDF statistics which have this property in order to improve EDF tests. Monte Carlo simulations show that the adjusted EDF statistics are more powerful than EDF ones in many cases, especially for heavy tail alternative distributions. We also consider the relations between the behavior of the tests and their extreme value points.