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1·Spatial distribution of TN content could be forecasted by using linear regression model.

利用线性回归模型，可以预测TN含量的空间分布。

2·A multivariate regression equation was deduced with a multivariate linear regression model.

通过多元线性回归模型，得出了多因子复合流变方程。

3·The comparison demonstrates that the model is superior to linear regression model in precision.

精度检验合格，经比较该模型预测精度优于线性回归模型的预测精度。

4·Returning to fraud detection, imagine a linear regression model with a transaction amount feature.

回到欺诈检测问题，设想一个具有交易金额特征的线性回归模型。

5·There is a regression constant in the linear regression model. But it is not significant in some conditions.

利用线性回归建模时，一般都采用有常数项的模型，而不去考虑它对回归的作用是否显著。

6·The missing data were analysed with sample selection model and compared with traditional linear regression model.

应用样本选择模型对模拟数据进行分析，并与传统线性回归模型进行比较。

7·Secondly, based on the system, evaluation model has set up by utilizing statistical linear regression model method.

其次，在此评价指标体系的基础上，利用统计中的线性回归模型的方法建立了评价模型。

8·This paper suggests a new AGARCH linear regression model, and USES nonparametric regression method to estimate the model.

本文提出一个新的非对称广义arch模型，并以非参数回归方法对模型进行估计。

9·This paper gives weighted least squares estimate and the method to choose optimum weighted function for linear regression model.

给出了线性回归模型中的加权最小二乘估计以及最优权数的选择。

10·This paper considers the estimation in the linear regression model under the criterion of minimizing the sum of absolute errors.

本文考虑在绝对误差和最小准则下的线性回归模型估计。