This paper investigates the asymptotic normality of the estimation error of steady-state models of industrial processes in quite mild conditions.

本文研究了在相当弱的条件下工业过程稳态模型估计误差的渐近正态性。

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Fan J and Gijbels I gave the asymptotic normality of local polynomial regression estimation in dependent time series, where the weighted function is bounded.

对相依时间序列数据，在一定的条件下已有人证明了局部多项式加权回归系数估计服从渐近正态分布，其中核函数是有界的。

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In this paper, we use the convex function to form the order statistic and the linear rank statistic, and the asymptotic normality of the statistics are proved.

本文用凸函数构造了线性次序统计量和线性秩统计量，并证明了它们的渐近正态性。

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