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Near-exact distributions for the independence and sphericity likelihood ratio test statistics

机译:独立性和球形似然比检验统计量的近似精确分布

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摘要

In this paper we show how, based on a decomposition of the likelihood ratio test for sphericity into two independent tests and a suitably developed decomposition of the characteristic function of the logarithm of the likelihood ratio test statistic to test independence in a set of variates, we may obtain extremely well-fitting near-exact distributions for both test statistics. Since both test statistics have the distribution of the product of independent Beta random variables, it is possible to obtain near-exact distributions for both statistics in the form of Generalized Near-Integer Gamma distributions or mixtures of these distributions. For the independence test statistic, numerical studies and comparisons with asymptotic distributions proposed by other authors show the extremely high accuracy of the near-exact distributions developed as approximations to the exact distribution. Concerning the sphericity test statistic, comparisons with formerly developed near-exact distributions show the advantages of these new near-exact distributions.
机译:在本文中,我们展示了如何基于对球形度的似然比检验分解为两个独立的检验,以及对似然比检验统计量对数的特征函数进行适当开发的分解,以检验一组变量中的独立性,我们如何对于两个测试统计数据,都可能获得非常合适的近乎精确的分布。由于两个检验统计量均具有独立Beta随机变量乘积的分布,因此有可能以广义近整数Gamma分布或这些分布的混合形式获得两个统计量的近似精确分布。对于独立性检验统计量,其他作者提出的数值研究和与渐近分布的比较表明,作为近似于精确分布的近似精确分布,具有极高的准确性。关于球形度测试统计数据,与以前开发的近精确分布的比较显示了这些新的近精确分布的优势。

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