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A class of optimization problems on minimizing variance based criteria in respect of parameter estimators of a linear model

机译:一类关于最小化基于差异基于线性模型的差异标准的优化问题

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摘要

We first consider an optimization problem in which we minimize the average or total variance of the estimators of some parameters of interest in a linear model. In some models, subsets of parameters may be of more interest in this respect than all parameters. We then consider a second optimization problem in which we construct designs achieving equality of variances of the estimators of two linear functions of the parameters. The approaches are formulated for a general regression model, and are explored through some models of interest.
机译:我们首先考虑一种优化问题,其中我们在线性模型中最小化一些兴趣参数的估计的平均值或总方差。在一些模型中,参数的子集可能比所有参数更感兴趣。然后,我们考虑第二优化问题,其中我们构建了实现参数的两个线性函数的估计变差平等的设计。该方法被制定为一般回归模型,并通过一些兴趣模型来探索。

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