Optimal Experimental Design for Polynomial Regression

Stephen M. Stigler

175 citations0/0 files storedJournal of the American Statistical Association

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Optimal Experimental Design Methods Statistical Methods and Applications Advanced Statistical Methods and Models

Abstract

The problem of choosing the optimal design to estimate a regression function which can be well-approximated by a polynomial is considered, and two new optimality criteria are presented and discussed. Use of these criteria is illustrated by a detailed discussion of the case that the regression function can be assumed approximately linear. These criteria, which can be considered as compromises between the incompatible goals of inference about the regression function under an assumed model and of checking the model's adequacy, are found to yield designs superior in certain respects to others which have been proposed to deal with this problem, including minimum bias designs.

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References

1959Optimum Experimental Designs 1959Optimum Designs in Regression Problems 1959A Basis for the Selection of a Response Surface Design 1992Optimum Experimental Designs 1966Optimal Experimental Designs 1961Optimum Designs in Regression Problems, II

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