Optimal designs for estimating the slope in nonlinear regression

dc.contributor.author	Dette, Holger	de
dc.contributor.author	Melas, Viatcheslav B.	de
dc.contributor.author	Shpilev, Petr	de
dc.date.accessioned	2009-10-29T10:01:23Z
dc.date.available	2009-10-29T10:01:23Z
dc.date.issued	2009-08-20	de
dc.description.abstract	We 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.identifier.uri	http://hdl.handle.net/2003/26475
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-811
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB 823; 19/2009	de
dc.subject	Chebyshev system	en
dc.subject	C-optimal designs	en
dc.subject	implicit function theorem	en
dc.subject	nonlinear regression	en
dc.subject.ddc	310	de
dc.subject.ddc	330	de
dc.subject.ddc	620	de
dc.title	Optimal designs for estimating the slope in nonlinear regression	en
dc.type	Text	de
dc.type.publicationtype	report	de
dcterms.accessRights	open access

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