摘要
目前有很多检验正态性假设的方法.这些方法主要分为两种类型:一种是基于经验分布函数的检验,另一种是基于相关性和回归的检验.在本文中,我们提出了一种新的基于L_(2) Wasserstein距离和第i个样本顺序统计量近似分布的两步检验方法.我们讨论在零假设下新检验方法的特性,并与最常用的几种检验分别在四个备择分布组进行功效比较.最后,将新方法应用于分析实际问题.仿真结果表明,新检验方法提高了鉴别不对称长尾备择分布的效率.
Many tests have been developed to check the normality assumption.These tests are mainly defined in two types:one is empirical distribution function test,the other is correlation and regression test.In this paper,we propose a new two-step test method based on the L_(2) Wasserstein distance and the approximate distribution of ith sample order statistic.We discuss the properties of the new test method under the null hypothesis,and compare the power with other most commonly tests for four alternative groups.Finally,the new method is applied to analyse the real problem.The simulation results show that the new test method improves the efficiency in identifying asymmetric long-tailed alternatives.
作者
杨超然
常广平
YANG Chaoran;CHANG Guangping(Information Department,Beijing University of Technology,Beijing,100124,China;Institute of Fundamental and Interdisciplinary Sciences,Beijing Union University,Beijing,100101,China)
出处
《应用概率统计》
CSCD
北大核心
2022年第2期179-194,共16页
Chinese Journal of Applied Probability and Statistics
基金
The project was supported by Beijing Union University Foundation(Grant No.11202JA2007).
