A Monte Carlo comparison of Jarque-Bera type tests and Henze-Zirkler test of multivariate normality
A Monte Carlo comparison of Jarque-Bera type tests and Henze-Zirkler test of multivariate normality
复制标题
Jarque-Bera 型检验和多元正态性 Henze-Zirkler 检验的蒙特卡洛比较
DOI：
10.1080/03610918.2017.1315771
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Kazuyuki Koizumi
中科院分区：
文献类型：
--
作者：
Zofia Hanusz;Rie Enomoto;Takashi Seo;Kazuyuki Koizumi
本文考虑了基于偏度和峰度的Jarque-Bera型多元正态性检验。Mardia和Srivastava提出的检验以及Jarque和Bera定义的基于偏度和峰度的组合检验已被考虑在内。在Monte Carlo模拟中，对于p = 2，3，4，5的性状数量和n = 10（5）50（10）100个样本量的每个组合，已经进行了10，000次运行以计算所考虑的检验的经验I型误差，以及针对不同替代分布的经验功效。模拟结果进行了比较的Henze-Zirkler的测试。应该强调的是，还没有一种试验在所考察的每一种条件组合下都比所有其他试验都好。
In the paper, tests for multivariate normality (MVN) of Jarque-Bera type, based on skewness and kurtosis, have been considered. Tests proposed by Mardia and Srivastava, and the combined tests based on skewness and kurtosis defined by Jarque and Bera have been taken into account. In the Monte Carlo simulations, for each combination ofp= 2, 3, 4, 5 number of traits andn= 10(5)50(10)100 sample sizes 10,000 runs have been done to calculate empirical Type I errors of tests under consideration, and empirical power against different alternative distributions. Simulation results have been compared to the Henze–Zirkler’s test. It should be stressed that no test yet proposed is uniformly better than all the others in every combination of conditions examined.