The data deletion model and the mean drift model are equivalent in a general linear regression model.
为了诊断具有异方差的线性回归模型的异常点，建立了具有异方差的均值漂移模型和数据删除模型。
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。
The general form of CUSI neuron model and its learning algorithm are given, and apply it to geological data analysis and get the better effect than linear regression.
提出了CUSI神经元模型的一般形式，给出其学习算法。通过实例将CUSI神经元模型应用到地质数据的分析上，取得了比线性回归更好的效果。
Objective to relax linear assumption of explanatory variables in general linear model and explore more-dimensional spline regression analysis model.
目的放宽经典线性模型中的多个解释变量的线性假定和探讨多维样条回归分析模型。
Objective to relax linear assumption of explanatory variables in general linear model and explore more-dimensional spline regression analysis model.
目的放宽经典线性模型中的多个解释变量的线性假定和探讨多维样条回归分析模型。
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