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Best Linear Unbiased Estimation and Prediction under a Selection Model
Biometrics, 1975Mixed linear models are assumed in most animal breeding applications. Convenient methods for computing BLUE of the estimable linear functions of the fixed elements of the model and for computing best linear unbiased predictions of the random elements of the model have been available.
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Journal of Statistical Planning and Inference, 2009
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Simple least squares estimation versus best linear unbiased prediction
Journal of Statistical Planning and Inference, 1981Abstract Necessary and sufficient conditions are developed for the simple least squares estimator to coincide with the best linear unbiased predictor. The conditions obtained are valid for a general linear model and are generalizations of the condition given by Watson (1972).
Baksalary, J. K., Kala, R.
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Best linear unbiased estimation for the Weibull process
Microelectronics Reliability, 1994Abstract Best linear unbiased estimators, approximative simultaneous confidence limits, acceptance regions, and prediction limits are given for the Weibull process. The approach is based on failure terminated observations, the statistic generalized total life, and the logarithmic gamma distribution.
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Mean driven balance and uniformly best linear unbiased estimators
Statistical Papers, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zmyślony, Roman +3 more
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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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