Parameter Estimation in Enzyme-Kinetics with Consideration of Heteroscedasticity and Low Dose Data

dc.contributor.author	Brunnert, Marcus	de
dc.contributor.author	Gilberg, Frank	de
dc.date.accessioned	2004-12-06T18:40:08Z
dc.date.available	2004-12-06T18:40:08Z
dc.date.issued	1999	de
dc.description.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-maximum-likelihood 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.	en
dc.format.extent	110057 bytes
dc.format.extent	779337 bytes
dc.format.mimetype	application/pdf
dc.format.mimetype	application/postscript
dc.identifier.uri	http://hdl.handle.net/2003/4941
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-6640
dc.language.iso	en	de
dc.publisher	Universitätsbibliothek Dortmund	de
dc.subject	heteroscedastic error variance	en
dc.subject	low dose data	en
dc.subject	Michaelis-Menten-kinetic	en
dc.subject	nonlinear regression model	en
dc.subject	pseudo-maximum-likelihood estimation	en
dc.subject	simulation study	en
dc.subject.ddc	310	de
dc.title	Parameter Estimation in Enzyme-Kinetics with Consideration of Heteroscedasticity and Low Dose Data	en
dc.type	Text	de
dc.type.publicationtype	report	en
dcterms.accessRights	open access

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