Linearization conditions for regression models with unknown variance parameter.
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.
scientific article; zbMATH DE number 1508454