线性无偏最小方差估计与最优加权最小二乘估计是线性模型下两种最常用的估计方法。
The linear unbiased minimum variance estimate and the optimally weighted least squares estimate are two of the most popular estimation methods for a linear model.
在给定的线性模型下，讨论了最优加权最小二乘估计与线性无偏最小方差估计性能比较。
The discussion on the property comparison between optimally weighted LS estimate and linear unbiased minimum variance estimate for a linear model is presented.
在这种情况下，最优加权最小二乘估计变成关于观测和输入的非线性估计，且与线性最小方差估计不可比。
In this case optimally weighted LS estimate is not a linear estimate of a parameter given input and observation anymore and can not be compared with linear minimum variance estimate.
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