本文研究了一般的随机效应多元线性模型中线性可估函数的最优线性无偏估计。
In this paper we investigated optimal linear unbiased estimation of the linear estimable function in general multivariate random effect linear model.
利用矩阵的向量化方法，研究了带线性约束的增长曲线模型中可估函数的线性估计在非齐次线性估计类中可容许的充要条件。
In this thesis, the admissibility and general admissibility of linear estimators in growth curve model with respect to inequality restriction are considered.
文摘：一般线性模型可估函数的可容许估计问题已有详细的讨论。对一般线性模型在矩阵损失下，得到了不可估函数的线性估计为可容许估计的充要条件。
Abstract: Under the matrix loss function, the necessary and sufficient conditions of linear admissible estimates of nonestimatible parameter functions for a general linear model are obtained.
利用中心削波并对估值器中的增益函数进行修正，可明显地减弱剩余噪声。
By using the center clipping and gain function modification of estimator, the residual noise can be reduced significantly.
利用中心削波并对估值器中的增益函数进行修正，可明显地减弱剩余噪声。
By using the center clipping and gain function modification of estimator, the residual noise can be reduced significantly.
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