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dc.contributor.authorDette, Holgerde
dc.contributor.authorMelas, Viatcheslav B.de
dc.contributor.authorShpilev, Petrde
dc.date.accessioned2009-10-29T10:01:23Z-
dc.date.available2009-10-29T10:01:23Z-
dc.date.issued2009-08-20de
dc.identifier.urihttp://hdl.handle.net/2003/26475-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-811-
dc.description.abstractWe consider the problem of estimating the slope of the expected response in nonlinear regression models. It is demonstrated that in many cases the optimal designs for estimating the slope are either on k or k - 1 points, where k denotes a number of unknown parameters in the model. It is also shown that the support points and weights of the optimal designs are analytic functions, and this result is used to construct a numerical procedure for the calculation of the optimal designs. The results are illustrated in exponential regression and rational regression models.en
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823; 19/2009de
dc.subjectChebyshev systemen
dc.subjectC-optimal designsen
dc.subjectimplicit function theoremen
dc.subjectnonlinear regressionen
dc.subject.ddc310de
dc.subject.ddc330de
dc.subject.ddc620de
dc.titleOptimal designs for estimating the slope in nonlinear regressionen
dc.typeTextde
dc.type.publicationtypereportde
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 823

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