Authors: Dette, Holger
Melas, Viatcheslav B.
Pepelyshev, Andrey
Title: Optimal designs for estimating the slope of a regression
Language (ISO): en
Abstract: 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. AMS Subject Classification: 62K05
Subject Headings: Estimating derivatives
Fourier regression
Locally optimal design
Polynomial regression
Standardized minimax optimal design
URI: http://hdl.handle.net/2003/25987
http://dx.doi.org/10.17877/DE290R-1952
Issue Date: 2009-01-13T07:58:21Z
Appears in Collections:Sonderforschungsbereich (SFB) 475

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