| 1. | The least square estimate of covariance matrix in the restricted growth curve model
有约束的生长曲线模型中协差阵的最小二乘估计 |
| 2. | The least square estimate of covariance matrices in the growth curve model with random effects
含有随机效应的增长曲线模型协差阵的最小二乘估计 |
| 3. | The least square estimate of the regression coefficient matrix in the extension of the growth curve model
推广增长曲线模型中回归系数阵的最小二乘估计 |
| 4. | The least square estimate of covariance matrix in an extended growth curve model and its optimal property
一个推广增长曲线模型协差阵的最小二乘估计及其优良性 |
| 5. | The method involves principal components analysis , phase space reconstruction and least squares estimate
方法包括3部分：主分量分析，相空间重构，最小二乘拟合。 |
| 6. | After an intensive analysis of several methods of computing the orientation image , we select the " least square estimate " method in our research
我们对多种求解指纹图像方向图的方法进行了深入的分析与比较，并最终选定了“最小平方估计法”作为我们求解指纹图像方向图的方法。 |
| 7. | Simulation results indicate the algorithm and simulation platform were available . at the last of this thesis , some methods of optimal rotation design were discussed , four methods of optimal design were analyzed under the least square estimate
在本文的最后,讨论了惯导平台系统最优多位置翻滚试验设计,在最小二乘估计中,分析了四种优化设计方法。 |
| 8. | Through proper linear transformation of the origional model , we obtain the educed models which are all sigular models . we peform the uniform theory of least squares getting the best linear unbiased estimates of the coefficents and the ordinary least squares estimates
因为这时模型协方差阵结构仍含有方差参数，因此我们的目标是寻求可行估计。我们通过对原模型做适当的线性变换，获得了导出模型，这些模型都是奇异线性模型。 |
| 9. | In chapter 4 , we study the outlier mining when the parameter estimate of the given linear model is not least square estimate ( lse ) but uniform biased estimate ( ube ) , and present the cook - distance based on the uniform biased estimate , which we use as an important tool in mining influence point
第四章研究了当线性模型的参数估计不是最小二乘估计而是泛岭估计时的异常挖掘,给出了针对泛岭估计的cook距离,用其作为挖掘强影响点的工具。 |
| 10. | In this paper , an integral scheme of 16 position error calibration and autonomous alignment for three axis platform is given . it may calibrate 33 errors in all . first , determine parameters with least square estimate , then bayes method , ridge regression estimation were discussed separately
本文设计了一个十六位置误差标定方案,可以分离出总计33项误差,首先用最小二乘估计方法进行参数辨识,而后,分别研究了基于bayes方法的误差系数辨识,基于岭估计的误差系数辨识。 |
