%0 Journal Article
%T Embedded Direct Search of Optimal Designs for Finite Noise Experiments
%A Franziska Schulz
%A Kurt Frischmuth
%J Archives of Transport
%D 2010
%I Versita
%R 10.2478/v10174-010-0008-z
%X We study experimental designs for the identification of nonlinear model parameters. As optimality criterion we assume minimality of the error in a huge number of identifications run on simulated data, which are generated with known parameters and a given error distribution. The optimal design depends on the nonlinear parameters. We find the optimal solution set by combining a path following strategy and a direct search method.
%K parameter identification
%K nonlinear regression
%K embedding method
%K direct search algorithm
%U http://versita.metapress.com/content/0q5w178414576530/?p=f91ac98718f04f31b78c6589c48deb5a&pi=7