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。
A reconstructing method for random weighting approximations is proposed in approach to the distributions of the parameter estimates in general linear regression model.
以广西实际资料具体阐述了线性自回归加权递推模型在大林业中的应用。
By using this material in Guangxi, the application of the linear autoregression model associated with weighting and recursive estimation was introduced for forestry.
主要考虑了同方差型的半参数线性回归模型中参数的随机加权最小二乘估计（RWLSE）。
The randomly weighted least square estimator (RWLSE) for the parametric component in semi-parametric regression models was mainly discussed.
研究了带有约束的均值漂移和方差加权的混合非线性回归模型．得到了相应的一阶和二阶诊断统计量。
We study restriction of Nonlinear Regression Diagnostic Models with case-weights and meanshifte simultanously, and some new diagnostic statistics are derved.
给出了线性回归模型中的加权最小二乘估计以及最优权数的选择。
This paper gives weighted least squares estimate and the method to choose optimum weighted function for linear regression model.
利用率点对模型参数估计的影响强弱，使用一种加权的线性回归模型参数估计算法。
Model parameters are computed using a weighted linear regression technology according to the different impacts of rate point to estimation of model parameters.
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。
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。
Rao and Zhao (1992) developed the random weighting method for M-estimates in regression models.
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