Abstract
The paper concludes our investigations in looking for the locally best linear-quadratic estimators of mean value parameters and of the covariance matrix elements in a special structure of the linear model (2 variables case) where the dispersions of the observed quantities depend on the mean value parameters. Unfortunately there exists no linear-quadratic improvement of the linear estimator of mean value parameters in this model.
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References
Kubáček L.: Foundations of Estimation Theory. Elsevier, Amsterdam, 1988.
Rao C.R. and Mitra S.K.: Generalized Inverse of Matrices and Its Applications. J. Wiley, New York, 1971.
Rinner K., Benz F.: Jordan/Eggert/Kneissl Handbuch der Vermessungskunde. Band VI, Stuttgart, 1966.
Wimmer G.: Linear model with variances depending on the mean value. Mathematica Slovaca 42 (1992), 223-238.
Wimmer G.: Uniformly best linear-quadratic estimator in a special structure of the regression model. Acta Math. Univ. Comenianae LXI (1992), 243-250.
Wimmer G.: Estimation in a special structure of the linear model. Mathematica Slovaca 43 (1993), 221-264.
Wimmer G.: Linear-quadratic estimators in a special structure of the linear model. Applications of Mathematics 40 (1995), 81-105.
Wimmer G.: Covariance matrix elements estimation: Special linear model without and with repeated measurement. Mathematica Slovaca 47 (1997), 339-371.
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Wimmer, G. Bad Luck In Quadratic Improvement of The Linear Estimator In A Special Linear Model. Applications of Mathematics 43, 1–7 (1998). https://doi.org/10.1023/A:1022290206923
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DOI: https://doi.org/10.1023/A:1022290206923