Based on the analysing of the data, selected relevant factors, made a series of tests and amendments with models, then created forest volume estimation optimal multivariate linear regression model.
在分析数据的基础上，选择了相关遥感因子和定性因子，并通过一系列模型的检验与修正，建立了公顷蓄积量估测的最优多元线性回归模型。
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。
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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