Startseite Mathematik Reparameterization of weakly nonlinear regression models with constraints
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Reparameterization of weakly nonlinear regression models with constraints

  • Lubomír Kubáček EMAIL logo und Gejza Wimmer
Veröffentlicht/Copyright: 27. August 2016
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Abstract

There are several ways how to redefine the Bates and Watts curvatures in models with constraints. One of possible approaches is based on a reparametrization of models. It enables us to construct linearization regions for the bias of parameter estimators, for the confidence regions, etc., in an easy way.

MSC 2010: Primary 62F10; 62J05

Supported by the Council of the Czech Government MSM 6 198 959 214



(Communicated by Gejza Wimmer)


Acknowledgement

Autor is indebted to RNDr. J. Marek, Ph.D. for his help in numerical calculation and to the reviewer who recognized many mistakes in the manuscript.

References

[1] Bates, D. M.—Watts, D. G.: Relative curvature measures of nonlinearity, J. Roy. Statist. Soc. Ser. B 42 (1980), 1–25.10.1111/j.2517-6161.1980.tb01094.xSuche in Google Scholar

[2] Fišerová, E.—Kubáček, L.—Kunderová, P.: Linear Statistical Models; Regularity and Singularities, Academia, Prague, 2007.Suche in Google Scholar

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[4] Kubáček, L.—Tesaříková, E.: Weakly nonlinear regression model with constraints I: nonlinear hypothesis, Discuss. Math. Probab. Stat. 25 (2005), 115–133.10.7151/dmps.1065Suche in Google Scholar

[5] Kubáček, L.—Tesaříková, E.: Weakly Nonlinear Regression Models, Palacký University, Olomouc, 2008.Suche in Google Scholar

[6] Rao, C. R.—Mitra, S. K.: Generalized Inverse of Matrices and Its Applications, J. Wiley, New York-London-Sydney-Toronto, 1971.Suche in Google Scholar

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Received: 2012-11-30
Accepted: 2013-11-15
Published Online: 2016-8-27
Published in Print: 2016-6-1

© Mathematical Institute Slovak Academy of Sciences

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