最后，本文还通过理论分析丛实例演示论证了在这个估计类中，各种回归系数估计有着和其他工作者所得到的相容的结论。
Finally, through the theory analysis and the example demonstration, we prove from this estimate class that we get the results which are interlinked with the results attained by other statisticians.
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.
本文在矩阵损失下研究了一般增长曲线模型中随机回归系数线性估计的可容许性。
We investigate the admissibility of the linear estimate of random regression coefficients under a matrix loss function in general growth curve models.
对应于方差参数这两种估计的回归系数的两种两步估计，它们的均方误差大致相当。
However, two-stage estimates of regression coefficients corresponding to these two estimates have approximate equal mean square error.
结果表明，在设计矩阵高度共线性时，用奇异值分解的迭代加细可以改进回归系数的估计。
Results show that iterative refinement using the SVD can improve regression coefficient estimates in the cases where the design matrix is highly collinear.
通过迭代加细过程还可以改进回归系数的估计。
Also, estimates of the regression coefficients can sometimes be improved through iterative refinement.
本文讨论增长曲线模型回归系数的线性估计的容许性。
In this paper, we consider the admissibility of linear estimates of regression coefficients in growth curve model.
第三章是关于回归系数的可容许估计，这包括统计线性模型不受约束和受约束的情形。
In the third part, we give the admissible estimators of regression coefficients in statistical linear model with or without constraints.
本文讨论多元回归系数线性估计的可容许性。
In this paper, we discuss the admissibility for linear estimates on multivariate regression coefficients.
对这类模型的统计建模，人们既关心回归系数的估计，更关心误差条件方差结构中未知参数的估计。
For this kind of modeling, people care for not only the estimation of regressive coefficient but also the estimation of unknown parameters in conditional skedasticity.
对两种类型资料边际回归模型都可以同时估计回归系数和关联参数。
Marginal regression models can be used to estimate regression coefficients and association parameters for two kinds of data.
本文主要研究了生长曲线模型中回归系数的参数估计问题。
In this paper, some researches on estimator of parameters in the growth curve model are considered.
结果表明，当样本大小大于50时，回归系数的最小二乘估计具有较高的估计精度；
Our research shows that when sample size is greater than 50, the least square estimate of regression coefficiencies has high estimate precision.
在线性回归中，常用最小二乘估计求线性方程的回归系数。
In linear regression, the least squares estimation is heavily innuenced with outlyers.
本文考虑一般回归模型中回归系数的方向的估计问题。
In this paper, the estimation of the direction of the regression coefficient of general regression model is considered.
本文讨论带约束生长曲线模型中回归系数线性估计的泛容许性，给出了回归系数的线性估计在线性估计类中是泛容许估计的充要条件。
In this paper, we will consider the universal admissibility for linear estimators of regression coefficients under growth curve model with respect to restricted parameter sets.
本文介绍了文献中常见的线性有偏估计，在此基础上提出和讨论了回归系数的泛岭估计，它是常见线性有偏估计的统一表达形式。
In this paper, based on the linear biased estimates in the present literature, we propose and discuss the universal ridge estimates which is a unitary expression.
本文主要研究了带约束线性模型回归系数岭估计的影响分析问题。
This article mainly studies the influence analysis of ridge estimation in restricted linear model.
对半相依回归线性系统，我们周期地使用迭加信息的方法，得出了回归系数广义协方差改进估计。
In this paper we repeatedly draw information from the seemingly unrelated regression equations and introduce a method that can be used to improve the covariance improvement estimate (CIE).
为了确定多重线性回归模型中回归系数矩阵的秩，本文提出了一个基于M估计的模型选择程序，且在较弱的条件下建立了回归系数矩阵的秩的估计的强相合性。
To determine the rank of regression coefficient matrix in a multivariate linear regression model, a model selection procedure is proposed based on the M-estimation.
建立不完全数据回归方程，给出回归系数的最佳无偏整体估计及其协方差矩阵。
The regression equation for incomplete data is established, and the best unbiased integral estimators of the regression parameters and their covariance matrix are also given.
建立不完全数据回归方程，给出回归系数的最佳无偏整体估计及其协方差矩阵。
The regression equation for incomplete data is established, and the best unbiased integral estimators of the regression parameters and their covariance matrix are also given.
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