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On the efficiency of Gini's mean difference

机译:关于基尼均值效率的差异

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The asymptotic relative efficiency of the mean deviation with respect to the standard deviation is 88 % at the normal distribution. In his seminal 1960 paper A survey of sampling from contaminated distributions, J. W. Tukey points out that, if the normal distribution is contaminated by a small -fraction of a normal distribution with three times the standard deviation, the mean deviation is more efficient than the standard deviation-already for . In the present article, we examine the efficiency of Gini's mean difference (the mean of all pairwise distances). Our results may be summarized by saying Gini's mean difference combines the advantages of the mean deviation and the standard deviation. In particular, an analytic expression for the finite-sample variance of Gini's mean difference at the normal mixture model is derived by means of the residue theorem, which is then used to determine the contamination fraction in Tukey's 1:3 normal mixture distribution that renders Gini's mean difference and the standard deviation equally efficient. We further compute the influence function of Gini's mean difference, and carry out extensive finite-sample simulations.
机译:在正态分布下,平均偏差相对于标准偏差的渐近相对效率为88%。 JW Tukey在1960年的开创性论文《从污染分布中抽样调查》中指出,如果正态分布被正态分布的小分数污染,且正态分布的标准偏差是标准偏差的三倍,则平均偏差比标准偏差更有效。已有偏差。在本文中,我们检查了基尼均值差(所有成对距离的均值)的效率。我们的结果可以通过说基尼的均值差结合了均值偏差和标准偏差的优点来概括。尤其是,通过残差定理推导了正常混合物模型中基尼平均差的有限样本方差的解析表达式,然后将其用于确定图基1:3正态混合物分布中的污染分数,从而得出基尼平均差和标准差同样有效。我们进一步计算基尼平均差的影响函数,并进行广泛的有限样本模拟。

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