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.
加权最小二乘回归。
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.
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.
提出一种基于局部加权回归预测球运动轨迹的学习方法，尤其是球与边界碰撞后的运动轨迹。
Thirdly, a learning method based on Locally Weighted Regression is proposed to forecast the motion of the ball, especially after the ball bump into wall.
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.
作者提出一种更简便的预测方法——加权一元线性回归预测法。
The author proposed a simpler forecast method -weighting single regression linear return forecast method.
考虑加权回归模型，定义了一种新的相对效率，并给出了相对效率的下界，同时讨论了新的相对效率与其它三种已有相对效率的关系。
For the linear weighted regression model, this paper defines a new relative efficiency, gives its lower bound and also discusses its relation to other three efficiencies.
本文提出了一种用加权多项式回归对球状模型和二级套合球状模型的变差函数进行最优拟合的方法。
The paper suggests an approach, utilizing the weighted polynomial regression for the best fitting of the variogram about spherical model or two-order nested spherical model.
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.
通过赋予合理权重，将C-D生产函数模型、多元回归模型和指数平滑模型加权组合。
The model which combined Cobb-Douglas production function, multiple regression model and exponential smoothing model can improve the accuracy of fix and forecast by proper weighs.
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.
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.
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。
Fan J and Gijbels I gave the asymptotic normality of local polynomial regression estimation in dependent time series, where the weighted function is bounded.
为了解决这个问题，本文提出了一种基于特征加权的支持向量回归机。
In order to solve the problem, support vector machine based on weighted feature is proposed in this paper.
本文则讨论加权非线性回归方差齐性的假设检验问题。
In this paper, we extend their result to nonlinear regression.
该模型通过隶属度加权来削弱个别异常数据对回归直线的影响，从而达到提高回归方程稳定性的目的。
By means of weighted subordination degree this model weakens the influence of distinct abnormal data affecting upon the regression straight line and...
该模型通过隶属度加权来削弱个别异常数据对回归直线的影响，从而达到提高回归方程稳定性的目的。
By means of weighted subordination degree this model weakens the influence of distinct abnormal data affecting upon the regression straight line and...
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