Algorithms for iteratively refining the parameter estimates and residuals from the fitting of a regression model using QR decomposition are described.
讨论用QR分解拟合回归方程时，参数估计和剩余的迭代加细算法。
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。
Zero-truncated count model could not only solve the issue of zero-truncated count distribution, but also the parameter estimates were more accurate, the fitting results were more reasonable.
采用零截尾计数模型分析，不仅可以解决零截尾计数分布问题，且参数估计结果更准确，拟合效果更合理。
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