Optimal designs for estimating the slope of a regression
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Date
2009-01-13T07:58:21Z
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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
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Keywords
Estimating derivatives, Fourier regression, Locally optimal design, Polynomial regression, Standardized minimax optimal design