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Linearization conditions for regression models with unknown variance parameter. (English) Zbl 1067.62547
A detailed analysis of criteria for a linearization of regression models is given. The frequently occuring situation when a variance parameter is unknown is solved. Several inequalities useful for users are found out. A test of intrinsic nonlinearity more powerful than that one used until now is also shown. The developed theory is nicely demonstrated on the Michaelis-Menten model.
62J02 General nonlinear regression
62J05 Linear regression; mixed models
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