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A New method for Testing Normality based upon a Characterization of the Normal Distribution

机译:一种基于正态分布特征检验正态性的新方法

摘要

The purposes of the thesis were to review some of the existing methods for testing normality and to investigate the use of generated data combined with observed to test for normality. The approach to testing for normality is in contrast to the existing methods which are derived from observed data only. The test of normality proposed follows a characterization theorem by Bernstein (1941) and uses a test statistic D*, which is the average of the Hoeffding’s D-Statistic between linear combinations of the observed and generated data to test for normality.Overall, the proposed method showed considerable potential and achieved adequate power for many of the alternative distributions investigated. The simulation results revealed that the power of the test was comparable to some of the most commonly used methods of testing for normality. The test is performed with the use of a computer-based statistical package and in general takes a longer time to run than some of the existing methods of testing for normality.
机译:本文的目的是回顾一些测试正常性的现有方法,并研究将生成的数据与观察到的数据相结合来测试正常性的方法。测试正常性的方法与仅从观察到的数据得出的现有方法相反。提出的正态性检验遵循Bernstein(1941)的一个定理定理,并使用检验统计量D *,它是观测数据和生成数据的线性组合之间的霍夫丁D-统计量的平均值,以检验正态性。该方法显示出可观的潜力,并为许多可供选择的分布提供了足够的功率。仿真结果表明,该测试的功能可与某些最常用的正常性测试方法相媲美。该测试是使用基于计算机的统计软件包来执行的,并且与某些现有的正常性测试方法相比,运行时间通常更长。

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    Melbourne Davayne A;

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  • 年度 2014
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