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On Some Tests of the Covariance Matrix Under General Conditions

机译:一般条件下协方差矩阵的一些检验

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We consider the problem of testing the hypothesis about the covariance matrix of random vectors under the assumptions that the underlying distributions are nonnormal and the sample size is moderate. The asymptotic expansions of the null distributions are obtained up to n ?1/2. It is found that in most cases the null statistics are distributed as a mixture of independent chi-square random variables with degree of freedom one (up to n ?1/2) and the coefficients of the mixtures are functions of the fourth cumulants of the original random variables. We also provide a general method to approximate such distributions based on a normalization transformation.
机译:我们考虑在基本分布为非正态且样本大小为中等的假设下测试关于随机向量的协方差矩阵的假设的问题。零分布的渐近展开得到nπ1/ 2。可以发现,在大多数情况下,无效统计量是作为独立卡方随机变量的混合而分布的,自由度为1(最大n 1/2),并且混合系数是该变量的第四累积量的函数。原始随机变量。我们还提供了一种基于归一化变换来近似此类分布的通用方法。

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