Results 251 to 260 of about 7,836,569 (290)

On equality of ordinary least squares estimator, best linear unbiased estimator and best linear unbiased predictor in the general linear model

Journal of Statistical Planning and Inference, 2009
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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, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Puntanen, Simo, Styan, George P. H., Werner, Hans Joachim   +2 more
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A bound for the Euclidean norm of the difference between the best linear unbiased estimator and a linear unbiased estimator

Journal of Geodesy, 2002
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A projector oriented approach to the best linear unbiased estimator

Statistical Papers, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Baksalary, Oskar Maria, Trenkler, Götz
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Best linear unbiased estimation for the Weibull process

Microelectronics Reliability, 1994
Abstract 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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Best Linear Unbiased Estimation for the Aitken Model

2020
Recall 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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Best linear unbiased quantile estimators for environmental standards

Environmetrics, 2002
AbstractRecent research has sought to develop a statistically based approach to setting environmental standards, prompted by Barnett and O'Hagan (1997) whose recommendations for a statistically verifiable ideal standard (SVIS) were endorsed by the Royal Commission on Environmental Pollution (1998).
Vic Barnett, Marion Bown
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Best Linear Unbiased Estimation and Prediction under a Selection Model

Biometrics, 1975
Mixed 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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Optimal sensor data quantization for best linear unbiased estimation fusion

2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601), 2004
Distributed 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.
Keshu Zhang, X. Rong Li
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Best Linear Unbiased Estimation of Location and Scale Parameters

1999
Let 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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