
Like any optimality result, it is crucial to lay out carefully the range of possiblealternatives, and the criterion by which those alternatives will be compared. Theclassical optimality result for estimating linear models is the Gauss-Markovtheorem, which takes the range of possibilities to be linear, unbiased estimatorsof β, and the criterion to be variance of the estimator. I will return to boththese choices at the end of this section.






本文深入探讨了高斯-马尔科夫定理这一经典线性模型估计的最优性准则。该定理界定了在线性且无偏的β估计量中,以估计量方差作为评判标准的最优选择。
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