João Tiago Mexia, João Lita da Silva (2006)
Discussiones Mathematicae Probability and Statistics
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Consistency of LSE estimator in linear models is studied assuming that the error vector has radial symmetry. Generalized polar coordinates and algebraic assumptions on the design matrix are considered in the results that are established.
Z. Pawłowski (1964)
Applicationes Mathematicae
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J. Jurečková (1983)
Acta Universitatis Carolinae. Mathematica et Physica
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Jerzy Baksalary, Radosław Kala (1980)
Banach Center Publications
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Lubomír Kubáček (2012)
Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
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Bad conditioned matrix of normal equations in connection with small values of model parameters is a source of problems in parameter estimation. One solution gives the ridge estimator. Some modification of it is the aim of the paper. The behaviour of it in models with constraints is investigated as well.
František Štulajter (1987)
Aplikace matematiky
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The method of least wquares is usually used in a linear regression model for estimating unknown parameters . The case when is an autoregressive process of the first order and the matrix corresponds to a linear trend is studied and the Bayes approach is used for estimating the parameters . Unbiased Bayes estimators are derived for the case of a small number of observations. These estimators are compared with the locally best unbiased ones and with the usual least squares estimators. ...
Lubomír Kubáček (2012)
Applications of Mathematics
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Estimators of parameters of an investigated object can be considered after some time as insufficiently precise. Therefore, an additional measurement must be realized. A model of a measurement, taking into account both the original results and the new ones, has a litle more complicated covariance matrix, since the variance components occur in it. How to deal with them is the aim of the paper.
Álex Costa, Albert Satorra, Eva Ventura (2003)
SORT
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This paper compares five small area estimators. We use Monte Carlo simulation in the context of both artificial and real populations. In addition to the direct and indirect estimators, we consider the optimal composite estimator with population weights, and two composite estimators with estimated weights: one that assumes homogeneity of within area variance and squared bias and one that uses area-specific estimates of variance and squared bias. In the study with real population, we found...