Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/77130
Authors: 
Brunnert, Marcus
Gilberg, Frank
Year of Publication: 
1999
Series/Report no.: 
Technical Report, SFB 475: Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund 1999,49
Abstract: 
In this paper we propose a simulation study in order to discuss four statistical models dealing with the problem of parameter estimation in enzyme-kinetics. The pseudo-maximumlikelihood estimators for the transform-both-sides-model and the weighted TBS-model are compared with least-square-estimators of the classical nonlinear regression model and the linearized Eadie-Hofstee-plot. Due to heteroscedasticity of enzyme-kinetic data in low dose experiments the proposed estimators are investigated.
Subjects: 
Nonlinear regression model
Pseudo-maximum-likelihood estimation
Heteroscedastic error variance
Michaelis-Menten-kinetic
Low dose data
Simulation study
Document Type: 
Working Paper

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