Authors: | Konstantinou, Maria Dette, Holger |
Title: | Locally optimal designs for errors-in-variables models |
Language (ISO): | en |
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. |
Subject Headings: | error-in-variable model D-optimality nonlinear regression optimal design |
URI: | http://hdl.handle.net/2003/33611 http://dx.doi.org/10.17877/DE290R-6876 |
Issue Date: | 2014-09-05 |
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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