同时，本文又将此思想应用到对谱分解估计的改进上。
This idea is also used to improve spectral decomposition estimator.
其中，对于观测向量协方差阵的谱分解估计，我们很容易得到它在一些损失下的风险函数。
Thereinto, for the spectral decomposition estimate of the covariance matrix , we can gain the risk functions under some losses.
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.
本方法不需要特征分解，并且得到的是通常意义上的功率谱(可用于估计信号的能量)。
In this method, eigen-decomposition does not have to be used, and the direction spectrum is the power spectrum in common sense (it can be used to estimate signal power).
可逆的向量滑动平均(MA)模型参数估计问题本质上是一个矩阵谱分解问题。
The parameter estimation problem to the invertible vector moving average (ma) model essentially is a matrix spectral factorization problem.
可逆的向量滑动平均(MA)模型参数估计问题本质上是一个矩阵谱分解问题。
The parameter estimation problem to the invertible vector moving average (ma) model essentially is a matrix spectral factorization problem.
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