中文摘要：

谱分解估计（SDE）是新近提出的关于线性混合模型参数的一种新的估计方法，此方法的一个突出特点是同时给出固定效应参数和方差分量的显式解估计．本文就含两个方差分量的线性混合模型，对谱分解估计的性质做了进一步的研究，获得了方差分量的SDE和方差分析估计相等的充分必要条件，证明了在一定的条件下方差分量的SDE为一致最小方差无偏估计．

英文摘要：

The spectral decomposition estimate （SDE） proposed by Wang and Yin is a new method of simultaneously estimating fixed effects and variance components in linear mixed models. In this paper, we furthe study the properties of SDE under linear mixed models with two variance components. We get the necessary and sufficient condition for the equality of the analysis of variance estimate and the SDE of variance components, and show that the SDE of variance components is a uniformly minimum variance unbiased estimte under some conditions.