智能广义岭估计 Intelligence generalized ridge regression
The robust generalized ridge estimate is proposed to detect gross error and compute exterior elements.
将广义岭估计与选权迭代法相结合提出了稳健广义岭估计的方法，用于探测外方位元素解算过程中存在的粗差，效果明显。
参考来源 - 基于卫星遥感影像的单片测图与修测技术的研究Firstly, we simply introduce the basic knowledge of the comparison of estimate and model. Then, we use matrix partial order theory to compare the generalized ridge estimation with the least square estimation in section III of this chapter.
首先,简单介绍了估计和模型比较的基础知识,然后在本章第三节利用矩阵偏序理论比较了广义岭估计与LS估计。
参考来源 - 统计学中的一些矩阵理论及其相关应用·2,447,543篇论文数据，部分数据来源于NoteExpress
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.
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.
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