There are several ways to establish the asymptotic normality of $L$-statistics, depending upon the selection of the weights generating function and the cumulative distribution function of the underlying model. Here, in this paper it is shown that the two of the asymptotic approaches are equivalent/equal for a particular choice of the weights generating function.

翻译：本文展示了$L$-统计量的渐近正态性有若干种建立方式，具体取决于权重生成函数的选择及基础模型的累积分布函数。文中证明，对于特定的权重生成函数选择，这两种渐近方法是等价/相等的。