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Light tails: all summands are large when the empirical mean is large

机译:轻尾巴:当经验均值较大时,所有被加数都较大

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It is well known that for a fixed number of independent identically distributed summands with light tail, large values of the sample mean are obtained only when all the summands take large values. This paper explores this property as the number of summands tends to infinity. It provides the order of magnitude of the sample mean for which all summands are in some interval containing this value and it also explores the width of this interval with respect to the distribution of the summands in their upper tail. These results are proved for summands with log-concave or nearly log concave densities. Making use of some extension of the Erdoes-Renyi law of large numbers it also explores the forming of aggregates in a sequence of i.i.d. random variables. As a by product the connection is established between large exceedances of the local slope of a random walk on growing bins and the theory of extreme order statistics.
机译:众所周知,对于固定数量的具有轻尾的独立相同分布的求和子,只有当所有求和子取大值时,才能获得较大的样本均值。本文探讨了这种性质,因为求和数趋于无穷大。它提供了样本均值的数量级,所有被加数都在某个间隔中包含该值,并且还针对该加数在其上尾部的分布探索了该间隔的宽度。这些结果对于具有对数凹面或接近对数凹面密度的乘数证明。利用大量的Erdoes-Renyi定律的扩展,它也探索了i.i.d序列中聚集体的形成。随机变量。作为副产品,在增长的垃圾箱上随机游走的局部斜率的大范围超出与极端顺序统计理论之间建立了联系。

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