Classification of linear estimators
Pavel Kovanic (1979)
Kybernetika
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Pavel Kovanic (1979)
Kybernetika
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Rafail Khasminskii (2004)
SORT
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A survey of some recent results on nonparametric on-line estimation is presented. The first result deals with an on-line estimation for a smooth signal S(t) in the classic 'signal plus Gaussian white noise' model. Then an analogous on-line estimator for the regression estimation problem with equidistant design is described and justified. Finally some preliminary results related to the on-line estimation for the diffusion observed process are described.
Norbert Stockinger, Rudolf Dutter (1987)
Kybernetika
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Pavel Tuček, Jaroslav Marek (2006)
Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
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The aim of the paper is to show some possible statistical solution of the estimation of the dispersion of the GPS receiver. The presented method (based on theory of linear model with additional constraints of type I) can serve for an improvement of the accuracy of estimators of coordinates acquired from the GPS receiver.
Roman Zmyślony, Stefan Zontek (2002)
Discussiones Mathematicae Probability and Statistics
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It is shown that a method of robust estimation in a two way crossed classification mixed model, recently proposed by Bednarski and Zontek (1996), can be extended to a more general case of variance components model with commutative a covariance matrices.
Viktor Witkovský (1998)
Kybernetika
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The paper deals with modified minimax quadratic estimation of variance and covariance components under full ellipsoidal restrictions. Based on the, so called, linear approach to estimation variance components, i. e. considering useful local transformation of the original model, we can directly adopt the results from the linear theory. Under normality assumption we can can derive the explicit form of the estimator which is formally find to be the Kuks–Olman type estimator.