Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Konstantinou, Maria | - |
dc.contributor.author | Dette, Holger | - |
dc.date.accessioned | 2014-09-05T11:39:31Z | - |
dc.date.available | 2014-09-05T11:39:31Z | - |
dc.date.issued | 2014-09-05 | - |
dc.identifier.uri | http://hdl.handle.net/2003/33611 | - |
dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-6876 | - |
dc.description.abstract | This paper considers the construction of optimal designs for nonlinear regres- sion models when there are measurement errors in the predictor. Corresponding (approximate) design theory is developed for maximum likelihood and least squares estimation, where the latter leads to non-concave optimisation problems. For the Michaelis-Menten, EMAX and exponential regression model D-optimal designs can be found explicitly and compared with the corresponding designs derived under the assumption of no measurement error in concrete applications. | en |
dc.language.iso | en | de |
dc.relation.ispartofseries | Discussion Paper / SFB 823;31/2014 | en |
dc.subject | error-in-variable model | en |
dc.subject | D-optimality | en |
dc.subject | nonlinear regression | en |
dc.subject | optimal design | en |
dc.subject.ddc | 310 | - |
dc.subject.ddc | 330 | - |
dc.subject.ddc | 620 | - |
dc.title | Locally optimal designs for errors-in-variables models | en |
dc.type | Text | de |
dc.type.publicationtype | workingPaper | de |
dcterms.accessRights | open access | - |
Appears in Collections: | Sonderforschungsbereich (SFB) 823 |
Files in This Item:
File | Description | Size | Format | |
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DP_3114_SFB823_Konstantinou_Dette.pdf | DNB | 355.85 kB | Adobe PDF | View/Open |
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