Please use this identifier to cite or link to this item:
Dette, Holger
Melas, Viatcheslav B.
Year of Publication: 
Series/Report no.: 
Technical Report // Sonderforschungsbereich 475, Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund 2008,21
In 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.
locally optimal design
standardized minimax optimal design
estimating derivatives
polynomial regression
Fourier regression
Document Type: 
Working Paper

Files in This Item:
156.44 kB

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.