前言：目的：本文介绍了识别COX模型中强影响点的诊断方法。
Objective: This paper introduces diagnostic methods of identifying the influence points of COX model.
从结果我们可以得出，对动态回归模型的每个强影响点的研究都是不可忽视的。
From the result we can learn that any studies on every strong influential point in the model of regression sliding ought not to be neglected.
随着数据挖掘技术在现代商业中的广泛应用，对异常点和强影响点的挖掘成了经济、统计等领域广泛研究的课题。
With the wide application of data mining to modern business, the researches of data mining for outlier and influential point have been paid close attention to by economic and statistical circles.
方法：利用COX回归模型的两种残差和经验影响函数识别COX模型的强影响点，并通过实例比较两种方法的优劣。
Method: Apply two kinds of residual theory and influence of COX model to diagnosing the influence point of COX model, and compares residual analysis to influence analysis.
利用强束缚量子点模型，忽略杂质对于电子波函数的影响，我们还讨论了如何利用核自旋构造量子位。
By making use of the strong bound quantum dot model and neglecting the effects of impurity on electron wave function, this thesis is also reported how to use the spin of nuclear as the quantum bit.
提出了应用试验手段选择强夯击数、夯点间距及有效影响深度等强夯参数的方法。
A method to choose the number of DC, the spacing of DC, the effective influence depth and other parameters through the experiment is presented.
使用高杠杆值对模型进行分析诊断，探测出数据中的强影响点后，再建立一个改良模型。
Using the leverage value to detect this model and finding the mainly influential observation, an improvable model is built.
将它们分解为两项之积，指出强影响点、异常点、高杠杆点间的内在联系；
The decompositions clarify the relationship of influential observations, outliers, and high leverage cases.
从强润湿性液体沸腾机理的角度对起始沸腾点的影响给出了相应的解释。
Corresponding explanations were given in view of boiling mechanism of highly-wetting liquid.
结论：影响函数可有效地诊断COX模型的强影响点，而残差分析效果平平，建议实际应用中采用前者。
Conclusion: Influence function may identify effectively the influential point, while the effect of residual analysis is not well. So we suggest using the former in practical application.
第四章研究了模型变换下点的影响分析，具体诊断出了中国消费数据幂变换模型下的强影响点群。
Furthermore, I study the data influential analysis on model transformation in Chapter 4 and pick out the influence observation group at the power transformation model of Chinese consumption data.
第四章研究了模型变换下点的影响分析，具体诊断出了中国消费数据幂变换模型下的强影响点群。
Furthermore, I study the data influential analysis on model transformation in Chapter 4 and pick out the influence observation group at the power transformation model of Chinese consumption data.
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