• This paper deals with the quantitative relations between regression coefficients and partial correlation coefficients in multivariate linear regression, and their statistical meanings.

    本文论述多元线性回归中的回归系数与偏相关系数之间的数量关系以及它们的统计意义。

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  • Then the corresponding multivariate linear regression equations are established.

    并建立相应的多元线性回归方程。

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  • The topic diffusion analysis technology based on diffusion map and multivariate linear regression has been studied.

    提出基于传播图和多元线性回归的话题传播分析技术。

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  • This paper presents the prediction of Si content of molten iron by adopting methods of multivariate linear regression and neural networks.

    文章分别用多元线性回归方法和神经元网络方法对铁水的硅含量进行预测。

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  • By using multivariate linear regression analysis, the mathematical model to classify and evaluate reservoir with well logging data was established.

    通过多元线性回归分析,建立了用多种测井信息划分、评价储层的数学模型。

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  • In BBS, we study the index system affecting topic diffusion to achieve the diffusion trend forecast based on multivariate linear regression theory.

    在论坛内,提炼影响传播行为的指标体系,并结合多元线性回归理论,实现了对传播趋势的预测。

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  • A model showing dynamic change of groundwater level for Shenyang area is set up, using the method of multivariate linear regression in random model.

    作者应用随机模型中多元线性回归的方法建立了沈阳地区地下水位动态变化模型。

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  • To determine the rank of regression coefficient matrix in a multivariate linear regression model, a model selection procedure is proposed based on the M-estimation.

    为了确定多重线性回归模型中回归系数矩阵的秩,本文提出了一个基于M估计的模型选择程序,且在较弱的条件下建立了回归系数矩阵的秩的估计的强相合性。

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  • We combine unitary nonlinear regression with multivariate linear regression, it can reduce the error sum of squares of the model and improve the precision of forecast.

    即把一元非线性回归和多元线性回归结合起来,构造一个混合回归模型,这样就减小了模型的残差平方和,从而提高预报的准确性。

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  • Based on this, forecast model for slope stability was studied by multivariate linear regression and BP neural network methods, and the results were compared with those by limit equilibrium method.

    在此基础上,分别运用多元线性回归和BP神经网络方法研究边坡稳定性预测模型,并将其结果与极限平衡分析方法进行对比。

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  • Based on this, forecast model for slope stability was studied by multivariate linear regression and BP neural network methods, and the results were compared with those by limit equilibrium method.

    在此基础上,分别运用多元线性回归和BP神经网络方法研究边坡稳定性预测模型,并将其结果与极限平衡分析方法进行对比。

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