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Non-positive upper bounds on expectations of low rank order statistics from DFR populations

机译:DFR人群对低阶顺序统计的期望的非正上限

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Danielak (Sharp upper mean-variance bounds on trimmed means from restricled families, Statistics 37 (2003), pp. 305-324) established strictly positive optimal upper mean-variance bounds on the expectations of order statistics with relatively large ranks coming from decreasing failure rate populations. She also proved that the respective evaluations of low rank order statistics cannot be positive. Here, we show that the zero bounds on the deviation of the expected small order statistic from the population mean expressed in the scale units based on the pth absolute central moments with p>1 cannot be improved, and determine strictly negative sharp bounds in terms of the mean absolute deviation units.
机译:Danielak(来自受限制家庭的修整均值的尖锐均值上限,Statistics 37(2003),pp.305-324)为阶数统计的期望建立了严格正的最优均值上限,相对较大的秩来自于减少失败率人口。她还证明了对低等级顺序统计数据的相应评估不会是肯定的。在这里,我们表明期望的小阶统计量与以p> 1的pth个绝对中心矩为单位的基于pth个绝对中心矩的比例单位表示的总体均值的偏差的零界无法得到改善,并且根据平均绝对偏差单位。

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