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Title: Linearized regression model with constraints of type II (English)
Author: Kubáček, Lubomír
Language: English
Journal: Applications of Mathematics
ISSN: 0862-7940 (print)
ISSN: 1572-9109 (online)
Volume: 48
Issue: 3
Year: 2003
Pages: 175-191
Summary lang: English
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Category: math
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Summary: A linearization of the nonlinear regression model causes a bias in estimators of model parameters. It can be eliminated, e.g., either by a proper choice of the point where the model is developed into the Taylor series or by quadratic corrections of linear estimators. The aim of the paper is to obtain formulae for biases and variances of estimators in linearized models and also for corrected estimators. (English)
Keyword: nonlinear regression model
Keyword: linearization
Keyword: constraints of type II
MSC: 62F10
MSC: 62J02
MSC: 62J05
idZBL: Zbl 1099.62522
idMR: MR1980366
DOI: 10.1023/A:1026050312419
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Date available: 2009-09-22T18:13:20Z
Last updated: 2020-07-02
Stable URL: http://hdl.handle.net/10338.dmlcz/134526
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Reference: [1] D. M.  Bates, D. G. Watts: Relative curvature measures of nonlinearity.J.  Roy. Statist. Soc. B42 (1980), 1–25. MR 0567196
Reference: [2] L.  Kubáček, L.  Kubáčková, J.  Volaufová: Statistical Models with Linear Structures.Veda, Bratislava, 1995.
Reference: [3] L.  Kubáček: One of the calibration problems.Acta Univ. Palack. Olomuc., Mathematica 36 (1997), 117–130. MR 1620541
Reference: [4] L.  Kubáček, L.  Kubáčková: Regression models with a weak nonlinearity.Technical Report Nr. 1998.1, Universität Stuttgart, 1998, pp. 1–67.
Reference: [5] L.  Kubáček, L.  Kubáčková: Statistics and Metrology.Palacký University in Olomouc–Publishing House, 2000. (Czech)
Reference: [6] C. R.  Rao: Unified theory of linear estimation.Sankhya A 33 (1971), 371–394. Zbl 0236.62048, MR 0319321
Reference: [7] C. R.  Rao: Generalized Inverse of Matrices and Its Applications.J.  Wiley, N.  York-London-Sydney-Toronto, 1971. Zbl 0236.15005, MR 0338013
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