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dc.contributor.authorDette, Holger-
dc.contributor.authorKiss, Christine-
dc.date.accessioned2008-02-12T11:40:44Z-
dc.date.available2008-02-12T11:40:44Z-
dc.date.issued2008-02-12T11:40:44Z-
dc.identifier.urihttp://hdl.handle.net/2003/25011-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-8058-
dc.description.abstractIn this paper optimal experimental designs for inverse quadratic regression models are determined. We consider two different parameterizations of the model and investigate local optimal designs with respect to the c-, D- and E-criteria, which reflect various aspects of the precision of the maximum likelihood estimator for the parameters in inverse quadratic regression models. In particular it is demonstrated that for a sufficiently large design space geometric allocation rules are optimal with respect to many optimality criteria. Moreover, in numerous cases the designs with respect to the different criteria are supported at the same points. Finally, the efficiencies of different optimal designs with respect to various optimality criteria are studied, and the efficiency of some commonly used designs are investigated.en
dc.language.isoende
dc.subjectChebyshev systemsen
dc.subjectC-optimalityen
dc.subjectD-optimalityen
dc.subjectE-optimalityen
dc.subjectOptimal designsen
dc.subjectRational regression modelsen
dc.subject.ddc004-
dc.titleOptimal experimental designs for inverse quadratic regression modelsen
dc.typeTextde
dc.type.publicationtypereporten
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 475

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