On the Functional Approach to Optimal Designs for Nonlinear Models

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dc.contributor.authorMelas, Viatcheslav B.de
dc.date.accessioned2004-12-06T18:38:47Z
dc.date.available2004-12-06T18:38:47Z
dc.date.issued2004de
dc.description.abstractThis paper concerns locally optimal experimental designs for non-linear regression models. It is based on the functional approach introduced 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 problem for many nonlinear models. A wide class of such models is here introduced. It includes, in particular,three parameters logistic distribution, hyperexponential and rational models. For these models we construct the analytical solution and use it for studying the efficiency of locally optimal designs. As a criterion of optimality the well known D-criterion is considered.en
dc.format.extent270659 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/2003/4869
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-7021
dc.language.isoende
dc.publisherUniversitätsbibliothek Dortmundde
dc.subjectnonlinear regressionen
dc.subjectlocally optimal designsen
dc.subjectfunctional approachen
dc.subjectthree parameters logistic distributionen
dc.subjecthyperexponential modelsen
dc.subjectrational modelsen
dc.subjectD-criterionen
dc.subjectimplicit function theoremen
dc.subject.ddc310de
dc.subject.rswkexperimental designsen
dc.titleOn the Functional Approach to Optimal Designs for Nonlinear Modelsen
dc.typeTextde
dc.type.publicationtypereporten
dcterms.accessRightsopen access

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