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线性模型中异方差方差估计量的比较AI 解读

Four methods for estimating heteroscedastic variances are discussed in this article: the MINQUE introduced by C.R. Rao [7], the AUE introduced by S.D. Horn, R.A. Horn, and D.B. Duncan [4], the average of the squared residuals, and the sample variance. Properties of these estimators, including translation invariance, existence, bias, consistency, existence of negative estimates, and mean square error (MSE) are compared. In particular, it is shown that the AUE has smaller MSE…

线性模型中的异方差方差估计AI 解读

We describe an estimator of heteroscedastic variances in the Gauss-Markov linear model where E(ε) = 0 and with σ i 2 and unknown. It may be thought of as an approximation to the MINQUE method which results in computational economy, positive estimates, and decreased mean square error. Properties of this almost unbiased estimator are stated. It is compared with other estimators, and extensions to more general models are discussed.