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dc.contributor.authorBrunnert, Marcusde
dc.contributor.authorGilberg, Frankde
dc.date.accessioned2004-12-06T18:40:08Z-
dc.date.available2004-12-06T18:40:08Z-
dc.date.issued1999de
dc.identifier.urihttp://hdl.handle.net/2003/4941-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-6640-
dc.description.abstractIn 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.extent110057 bytes-
dc.format.extent779337 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/postscript-
dc.language.isoende
dc.publisherUniversitätsbibliothek Dortmundde
dc.subjectheteroscedastic error varianceen
dc.subjectlow dose dataen
dc.subjectMichaelis-Menten-kineticen
dc.subjectnonlinear regression modelen
dc.subjectpseudo-maximum-likelihood estimationen
dc.subjectsimulation studyen
dc.subject.ddc310de
dc.titleParameter Estimation in Enzyme-Kinetics with Consideration of Heteroscedasticity and Low Dose Dataen
dc.typeTextde
dc.type.publicationtypereporten
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 475

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