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Title: On a linearization of regression models (English)
Author: Kubáček, Lubomír
Language: English
Journal: Applications of Mathematics
ISSN: 0862-7940 (print)
ISSN: 1572-9109 (online)
Volume: 40
Issue: 1
Year: 1995
Pages: 61-78
Summary lang: English
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Category: math
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Summary: An approximate value of a parameter in a nonlinear regression model is known in many cases. In such situation a linearization of the model is possible however it is important to recognize, whether the difference between the actual value of the parameter and the approximate value does not cause significant changes, e.g., in the bias of the estimator or in its variance, etc. Some rules suitable for a solution of this problem are given in the paper. (English)
Keyword: nonlinear regression model
Keyword: linearization
Keyword: parameter effect curvature
Keyword: intrinsic curvature
MSC: 62J02
MSC: 62J05
idZBL: Zbl 0819.62054
idMR: MR1305650
DOI: 10.21136/AM.1995.134279
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Date available: 2009-09-22T17:46:37Z
Last updated: 2020-07-28
Stable URL: http://hdl.handle.net/10338.dmlcz/134279
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Reference: [1] Bates, D. M. and Watts, D. G.: Relative curvature measures of nonlinearity.J. Roy. Stat. Soc. B 42 (1980), 1–25. MR 0567196
Reference: [2] Janko,J.: Statistické tabulky.Praha, Academia, 1958. MR 0150924
Reference: [3] Pázman, A.: Nonlinear Statistical Models.Kluwer Academic Publishers, Dordrecht-Boston-London and Ister Science Press, Bratislava, 1993. MR 1254661
Reference: [4] Potocký, R., To Van Ban: Confidence regions in nonlinear regression models.Appl. of Math. 37 (1992), 29–39. MR 1152155
Reference: [5] Rao, C.R.: Linear Statistical Inference and Its Applications (2nd Edition).J. Wiley, New York, 1973. MR 0346957
Reference: [6] Scheffé, H.: The Analysis of Variance (fifth printing).J. Wiley, New York-London-Sydney, 1967. MR 1673563
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