方差分量模型的随机效应的协方差为单位阵时《线性模型引论》已进行研究。
Variance component model of the random effects of covariance matrix unit for the "Linear model introduction" matrix has been studied.
将广义线性混合模型应用于核心家系资料建立遗传方差分量模型，运用MCMC方法进行参数估计。
Methods We applied generalized linear mixed models for the nuclear family data to set up the genetic variance component model and estimated parameters using MCMC.
线性模型是很重要的一类统计模型，它包括线性回归模型、方差分析模型、协方差分析模型和方差分量模型等等。
Linear models are especially important statistical models, including linear regression model, variance and analysis, covariance and analysis, and variance and component one etc.
这种模型的未知参数分两类，一类是固定效应，一类是方差分量。
The unknown parameters of this model are divided into two categories: one is the fixed effects, and the other is the variance components.
将线性混合模型中随机效应的协方差阵推广为正定阵，运用方差分析估计的方法给出了方差分量的估计。
In this paper, the covariance matrix of random effect in linear mixed model is extended to positive matrix. We construct the estimation of variance components based on the idea of ANOVA estimation.
通过附有条件的间接平差模型进一步证明各类方差-协方差分量估计公式之间的等价性。
In this paper, through the model of parameter adjustment with constraints among the parameters, a further proof on the equivalence of the formulas of variance-covariance components is gives.
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。
Spectral decomposition estimators of variance component matrix in mixed linear model are generalized to multivariate mixed linear model.
对含两个方差分量的一般线性混合模型，我们给出其方差分量的改进估计，主要对组合谱分解估计进行改进。
We compare the spectral decomposition estimate by the analysis of variance estimate in the linear mixed model with two variance components.
对含两个方差分量的一般线性混合模型，我们给出其方差分量的改进估计，主要对组合谱分解估计进行改进。
We compare the spectral decomposition estimate by the analysis of variance estimate in the linear mixed model with two variance components.
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