在一定条件下证明了此岭估计的相合性。
Under the general condition, the consistency of the ridge estimation is proved.
第二章介绍了矩阵知识、岭估计和若干引理。
Then the knowledge of the matrix, ridge estimation and several lemmas are introduced.
但计算逆矩阵和岭脊的选择是广义岭估计的两个难点。
It is difficult to compute inverse matrix and select ridges.
三种方法分别是稳健主成分估计、稳健岭估计和稳健根方估计。
Finally, we obtained three robust biased model fitting methods which were called as robust principal component estimate, robust ridge estimate and robust root-root estimate respectively.
第五章讨论了均值漂移对带约束线性模型条件岭估计的影响问题。
The fifth chapter discusses the influence of mean shift disturbance to conditional ridge estimation in restricted linear model.
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.
在分析LS估计存在缺陷的基础上，提出采用岭估计建立郁闭度估测方程。
Then, based on the analysis of possible limitation of LS estimation, the ridge estimation is put forward to establish the equation of canopy density estimation.
给出了剔除前后岭估计的广义相关系数的表达式，并得到了某些一般的结果。
The expression of generalized correlation coefficient between the ridge estimators before and after deleting datum is given. Some general results are acquired, too.
基于所提出的条件岭估计，分析了三种扰动情形对条件岭估计的影响，并给出了相关结论。
Based on the proposed conditional ridge estimation, we analyse the influence of the three kinds of disturbance on the conditional ridge estimation, and give the relevant conclusions.
通过建立广义岭估计模型，分析得到平均学费和生均培养费成负相关，与国家生均拨款成正相关。
Through generalized ridge estimator model, we obtain that average tuition and training expense, nation allocation per student respectively have negative and positive correlation.
研究这一估计的性质，证明利用0-K型广义岭估计技术可以改进广义岭估计（在均方残差意义下）。
The 0-K class of estimators if studied, it will be proved that under the mean square residua criterion the estimators can be improved via the generalized ridge regression technique.
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.
针对法方程呈现病态且观测值受到污染而不严格服从正态分布的情况，探讨运用拟准检定法抗御粗差，用岭估计改善法方程的病态性。
This paper discusses the resistance of gross errors with quasi accurate detection and the improvement of ill conditioned equation with ridge estimate when the equation is ill conditioned and polluted.
本文以多元线性回归模型的典则形式为研究对象，从减小均方误差的角度出发，在一定的范围内分析了岭参数K 的存在性和岭估计的优良性。
The investigation object of this paper is the standard canonical form. In order to the mean square error, I analyze the existence and choiceness of ridge regression K in some spectrum.
岭回归分析是一种非线性的有偏估计方法。
Ridge Regression Analysis is a nonlinear partial estimation method.
讨论岭型主成分估计在一类降维估计中的方差性质，证明了它的方差和在这类降维估计中最小。
This paper deals with the variance property of combining ridge and principal components estimate in the class of reduced-dimension estimates.
研究岭型主成分估计在岭型降维估计类中的性质。
The property of combining ridge and principal components estimate is studied in the ridged class of reduced-dimension estimators.
本文研究了在均方误差意义下岭型主成分估计在岭型降维估计类中的最优性。
The optimality of the MSE of combining ridge and principal components in the class of combining ridge and reduced dimension estimators is dealt with in this paper.
证明了在一类岭型降维估计中，岭型主成分估计的方差和最小。
It is proved that the combining ridge and principal components regression have the minimum variance sum in the class of reduced-dimension estimators.
研究岭型主成分估计在降维估计类中的方差最优性，证明了它的方差阵在降维估计类中最小，方差阵的特征值最小，方差和及方差积最小。
This paper considers the classification compression principal component estimate of regression coefficient in growth curve model and proves that it is superior to least squares estimate.
研究岭型主成分估计在降维估计类中的方差最优性，证明了它的方差阵在降维估计类中最小，方差阵的特征值最小，方差和及方差积最小。
This paper considers the classification compression principal component estimate of regression coefficient in growth curve model and proves that it is superior to least squares estimate.
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