| 1. | Least - square estimation
最小二乘估计 |
| 2. | The method consists of two stages : sub - structural inversion of ground motion using least - square estimation , and parameter identification using extended kalman filter
本文所建立的方法分为两个阶段：地震动子结构反演和单元结构参数识别。 |
| 3. | Ridge regression analysis is modified least - squares estimation . it can offer a stable forecasting when there is strong correlation between variables
岭回归分析是一种修正的最小二乘估计法,当自变量系统中存在多重相关性时,它可以提供一个更为稳定的预测。 |
| 4. | The parameter of local model can be calculated by gradient descent in neighborhood with the sofm weight together , or estimated by least - squared estimation ( lse )
局部模型的参数既可和映射网络权值一起在邻域内采用梯度下降法修正，也可结合最小二乘法得到其最佳估计。 |
| 5. | Abstract : concerning the least - square estimation of unknown parameters in the linear model , this article discusses the relation between two kinds of relative efficiencies and one generalized correlation coefficient
文摘:讨论了线性模型中未知参数的最小二乘估计的两种相对效率与一种广义相关系数的关系 |
| 6. | Further more , with the knowledge of the relations between new and old samples , the article put forward the iteration algorithm of the weight in ordered samples " weighted least - square estimation , the model if good at forecasting
其次，在新样品与原样品的关系确知的情况下，该文提出了有序样品的加权估计中权重的一种迭代取法，再进行新预测，效果显著。 |
| 7. | A comparision between the partly - weigthed least - squares estimation and the kalman filter is made on precise kinematic gps positioning with the fixed ambiguities , which shows that the positioning results from the partly - weigthed least squares , which accuracy is at the level of 10 cm , are much more accurate than the results from the kalman filter , which accuracy is at the level of a few meters
针对高精度动态定位结果的精度，对最小二乘法和经典kalman滤波这两种算法进行了综合分析和比较。算例显示，在高精度gps动态测量中，最小二乘法可以提供厘米级精度的位置结果，而kalman滤波算法不但不能提高定位结果的精度，反而会给定位结果引入米级的偏差。 |
| 8. | The main research contents include : study the modeling and measure of tendency of customer group ' s requirements . use the method of least - squares estimation in conjoint analysis to model and measure the tendency of customer group ' s requirements and transform the fuzzy requirements of customer group into numerical attribute importance and level utility . solve the problems of estimation and optimization of regression model
研究的主要内容包括：研究了客户群体需求倾向的建模和量化过程：应用联合分析法的最小二乘回归模型建模和量化客户群体需求倾向，将模糊的客户群体需求倾向转化为量化的属性重要度和水平效应值，并解决了模型的有效性评估和优化问题。 |
