Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/49314 
Year of Publication: 
2004
Series/Report no.: 
Technical Report No. 2004,13
Publisher: 
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, Dortmund
Abstract: 
This paper concerns locally optimal experimental designs for non- linear regression models. It is based on the functional approach intro- duced in (Melas, 1978). In this approach locally optimal design points and weights are studied as implicitly given functions of the nonlinear parameters included in the model. Representing these functions in a Taylor series enables analytical solution of the optimal design prob- lem for many nonlinear models. A wide class of such models is here introduced. It includes, in particular,three parameters logistic distri- bution, hyperexponential and rational models. For these models we construct the analytical solution and use it for studying the e_ciency of locally optimal designs. As a criterion of optimality the well known D-criterion is considered.
Subjects: 
nonlinear regression
experimental designs
locally optimal designs
functional approach
three parameters logistic distribution
hyperexponential models
rational models
D-criterion
implicit function theorem
Document Type: 
Working Paper

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