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TRANSFER THEOREM CONCERNING ASYMPTOTIC EXPANSIONS FOR THE DISTRIBUTION FUNCTIONS OF STATISTICS BASED ON SAMPLES WITH RANDOM SIZES

机译:基于随机尺寸的样本转移关于统计数据分布函数的渐近扩展的定理

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In the paper, we discuss the transformation of the asymptotic expansion for the distribution of a statistic admitting Edgeworth expansion if the sample size is replaced by a random variable.We demonstrate that all those statistics that are regarded as asymptotically normal in the classical sense, become asymptotically Laplace or Student if the sample size is random. Thus, the Laplace and Student distributions may be used as an asymptotic approximation in descriptive statistics being a convenient heavy-tailed alternative to stable laws.
机译:在本文中,如果样本大小被随机变量取代,我们讨论了偶数宣传统计信息的渐近扩张的转换。我们证明了在经典意义上被视为渐近正常的所有这些统计数据变为如果样本大小是随机的,则渐近的Laplace或学生。因此,拉普拉斯和学生分布可以用作描述性统计中的渐近近似是一种方便的重尾替代,以稳定定律。

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