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Two matrix-based proofs that the linear estimator Gy is the best linear unbiased estimator
Journal of Statistical Planning and Inference, 2000zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Puntanen, Simo +2 more
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Best Linear Unbiased Estimation for the Aitken Model
2020Recall from Chap. 7 that the least squares estimators of estimable functions are best linear unbiased estimators (BLUEs) of those functions under the Gauss–Markov model. But it turns out that this is not necessarily so under linear models having a more general variance–covariance structure, such as the Aitken model.
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A projector oriented approach to the best linear unbiased estimator
Statistical Papers, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Baksalary, Oskar Maria, Trenkler, Götz
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Optimal sensor data quantization for best linear unbiased estimation fusion
2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601), 2004Distributed estimation is useful for surveillance using sensor networks. Due to the capacity constraints at the communication links, the data from the sensors are transmitted at a rate insufficient to convey all the observations reliably. Therefore, the observations are vector quantized and the estimation is done using the compressed measurements.
K. Zhang, X.R. Li
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Best Linear Unbiased Estimation of Location and Scale Parameters
1999Let us now assume that we have a random sample of size n, X 1, X 2,…, X n , from a three-parameter lognormal distribution [obtained by introducing location and scale parameters in (2.3)] with probability density function $$ \begin{gathered} f(x|\mu ,\sigma ,k) \hfill \\ \,\,\,\,\,\, = \frac{1}{{\left( {{{(k - 1)}^{{\raise0.7ex\hbox{${ - 1 ...
N. Balakrishnan, William W. S. Chen
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A Characterization of Best Linear Unbiased Estimators in the General Linear Model
1980A characterization of best linear unbiased estimators is given in the case of the general linear model. In addition necessary and sufficient conditions are derived for a given estimable function to have a best linear unbiased estimator. In particular models for which each estimable function has a best linear unbiased estimator are characterized.
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