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。
Results show that iterative refinement using the SVD can improve regression coefficient estimates in the cases where the design matrix is highly collinear.
结果表明，在设计矩阵高度共线性时，用奇异值分解的迭代加细可以改进回归系数的估计。
A robust parameters estimation algorithm is proposed in this paper, which is based on uniform design for a linear regression model in the case of its coefficient matrix with random disturbance.
针对一个线性回归模型的系统矩阵存在的随机扰动情况，提出一种基于均匀设计的稳健参数估计算法。
The Minimax admissibility of linear estimates with respect to restricted multivariate regression coefficient under matrix loss function is considered.
本文研究了带有不等式约束的生长曲线模型中线性估计的容许性与泛容许性问题。
The Minimax admissibility of linear estimates with respect to restricted multivariate regression coefficient under matrix loss function is considered.
本文研究了带有不等式约束的生长曲线模型中线性估计的容许性与泛容许性问题。
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