Full metadata record
DC Field | Value | Language |
---|---|---|
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.identifier.uri | http://hdl.handle.net/2003/4941 | - |
dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-6640 | - |
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.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 | - |
Appears in Collections: | Sonderforschungsbereich (SFB) 475 |
Files in This Item:
File | Description | Size | Format | |
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99_49.pdf | DNB | 107.48 kB | Adobe PDF | View/Open |
tr49-99.ps | 761.07 kB | Postscript | View/Open |
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