mixed linear model

This paper studies Bayes local influence in mixed linear model.

该文研究混合线性模型效应参数的Bayes局部影响评价问题。

Conclusion We should give attention to the algorithm and error distribution for data, so that generalized mixed linear model got the reasonable application.

结论GLIMMIX可分析多种离散型系统结构数据，但还应注意算法和数据的误差分布，才能使广义混合线性模型得以合理地应用。

the convergence rate of variance component's empirical bayes estimators in mixed-linear model

线性混合模型中方差分量的经验Bayes估计的收敛速度

mixed linear model and its application to repeated measurements in single-sample

单样本重复测量资料的混合线性模型及其应用

compared with the mixed linear model analysis, the analysis of variance could result in higher type i or ii statistical error rates.

相对线性混合模型分析法，方差分析法分析该试验时，依测验的效应不同会导致第一类或第二类统计错误率的增大。

Conclusion Mixed linear model can be used to analyze repeated measurement data in single-sample.

结论混合线性模型可以有效地、全面地分析单样本重复测量资料.

spectral decomposition estimators of variance component matrix in mixed linear model are generalized to multivariate mixed linear model.

考虑含有两个方差分量矩阵的多元混合模型，将一元混合模型下的谱分解估计推广到多元模型下。

analysis of irrigation experiment using general mixed linear model

田间灌溉试验资料广义混合线性模型分析

results the reasonable results were obtained for repeated measurements in single-sample by the methods of mixed linear model.

结果通过混合线性模型拟合，使单样本重复测量资料得以合理分析。