T-optimal discriminating designs for Fourier regression models

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dc.contributor.authorDette, Holger
dc.contributor.authorMelas, Viatcheslav B.
dc.contributor.authorShpilev, Petr
dc.date.accessioned2016-01-06T08:26:42Z
dc.date.available2016-01-06T08:26:42Z
dc.date.issued2015
dc.description.abstractIn this paper we consider the problem of constructing T-optimal discriminating designs for Fourier regression models. We provide explicit solutions of the optimal design problem for discriminating between two Fourier regression models, which differ by at most three trigonometric functions. In general, the T-optimal discriminating design depends in a complicated way on the parameters of the larger model, and for special configurations of the parameters T-optimal discriminating designs can be found analytically. Moreover, we also study this dependence in the remaining cases by calculating the optimal designs numerically. In particular, it is demonstrated that D- and Ds-optimal designs have rather low efficiencies with respect to the T-optimality criterion.en
dc.identifier.urihttp://hdl.handle.net/2003/34437
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-16493
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823;49/2015en
dc.subjectT-optimal designen
dc.subjecttrigonometric modelsen
dc.subjectChebyshev polynomialen
dc.subjectlinear optimality criteriaen
dc.subjectmodel discriminationen
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.titleT-optimal discriminating designs for Fourier regression modelsen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access

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Sonderforschungsbereich (SFB) 823