Rao and Zhao (1992) developed the random weighting method for M-estimates in regression models.

提出了一种用随机加权的方法去逼近线性回归模型中M-估计的渐近分布。

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In this paper we find an uniformly random weighting method to statistics admitting asymptotic normality and study its consistency and convergence rates of uniformity and nonuniformity.

对一类具有渐近正态的统计量，找到了适用于它们的共同的随机加权逼近方法，并研究了它的相合性、一致及非一致逼近速度。

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A reconstructing method for random weighting approximations is proposed in approach to the distributions of the parameter estimates in general linear regression model.

对一般线性回归模型中有关参数估计分布的模拟问题，给出一种随机加权逼近的再构造方法。

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