Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Gilberg, Frank | de |
dc.contributor.author | Urfer, Wolfgang | de |
dc.date.accessioned | 2004-12-06T18:38:57Z | - |
dc.date.available | 2004-12-06T18:38:57Z | - |
dc.date.issued | 1998 | de |
dc.identifier.uri | http://hdl.handle.net/2003/4880 | - |
dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-5320 | - |
dc.description.abstract | We discuss an extansion of the nonlinear random effects model from Lindstrom and Bates (1990) by adding a flexible transformation to both sides of the model (see Carroll and Ruppert (1988)) and describe a procedure for parameter estimation. This method combines pseudo maximum likelihood estimators for the transform-both-sides and weighting model and maximum likelihood (or restricted maximum likelihood) estimatiors for the linear mixed effects models. A validation of this new method is performed by analyzing a simulated set of enzyme kinetic data published by Jones (1993). | en |
dc.format.extent | 1456179 bytes | - |
dc.format.extent | 1784706 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.format.mimetype | application/postscript | - |
dc.language.iso | en | de |
dc.publisher | Universitätsbibliothek Dortmund | de |
dc.subject | enzyme kinetics | en |
dc.subject | nonlinear regression | en |
dc.subject | Pseudo likelihood estimation | en |
dc.subject | random effects | en |
dc.subject | repeated measures data | en |
dc.subject | transformation and weighting | en |
dc.subject.ddc | 310 | de |
dc.title | Heteroscedastic nonlinear regression models with random effects | 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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98_17.pdf | DNB | 1.42 MB | Adobe PDF | View/Open |
tr17-98.ps | 1.74 MB | Postscript | View/Open |
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This item is protected by original copyright
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