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Simultaneous multivariate tests under the normality assumption

机译:在正常假设下同时多变量测试

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In this study, we propose several simultaneous tests for the mean vector and covariance matrix of multivariate normal data. First of all, we consider the likelihood ratio (LR) test with a limiting distribution, and estimate one using the Monte-Carlo (MC) method for the null distribution. Next, we consider a union-intersection (UI) test by identifying the LR statistic as a product of two functions of random quantities. In addition, we propose simultaneous tests with combination functions. Then, we illustrate our procedure with an example, and compare the efficiency through a simulation study. Finally, we discuss interesting features for the proposed simultaneous tests with related topics and a method for obtaining the LR statistics.
机译:在这项研究中,我们提出了几种同时测试了多元常规数据的平均载体和协方差矩阵。首先,我们考虑使用限制分布的似然比(LR)测试,并使用Monte-Carlo(MC)方法来估计一个用于空分布的方法。接下来,我们考虑通过将LR统计标识为随机量的两个功能的乘积来考虑一个Union-InterSection(UI)测试。此外,我们提出了与组合功能的同时测试。然后,我们用示例说明了我们的过程,并通过模拟研究进行比较效率。最后,我们讨论了具有相关主题的建议的同时测试的有趣功能和获取LR统计的方法。

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