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dc.contributor.authorDette, Holgeren
dc.contributor.authorMelas, Viatcheslav B.en
dc.date.accessioned2009-05-26-
dc.date.accessioned2010-07-15T10:08:03Z-
dc.date.available2010-07-15T10:08:03Z-
dc.date.issued2008-
dc.identifier.urihttp://hdl.handle.net/10419/36619-
dc.description.abstractIn the common linear regression model we consider the problem of designing experiments for estimating the slope of the expected response in a regression. We discuss locally optimal designs, where the experimenter is only interested in the slope at a particular point, and standardized minimax optimal designs, which could be used if precise estimation of the slope over a given region is required. General results on the number of support points of locally optimal designs are derived if the regression functions form a Chebyshev system. For polynomial regression and Fourier regression models of arbitrary degree the optimal designs for estimating the slope of the regression are determined explicitly for many cases of practical interest.en
dc.language.isoengen
dc.publisher|aTechnische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen |cDortmunden
dc.relation.ispartofseries|aTechnical Report |x2008,21en
dc.subject.ddc519en
dc.subject.keywordlocally optimal designen
dc.subject.keywordstandardized minimax optimal designen
dc.subject.keywordestimating derivativesen
dc.subject.keywordpolynomial regressionen
dc.subject.keywordFourier regressionen
dc.titleOptimal designs for estimating the slope of a regression-
dc.typeWorking Paperen
dc.identifier.ppn600405931en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:zbw:sfb475:200821en

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