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Optimal discrimination designs

Holger Dette, Stefanie Titoff

The Annals of Statistics · 2009 · Volume 37 · Issue 4

DOI: 10.1214/08-AOS635

Abstract

We consider the problem of constructing optimal designs for model discrimination between competing regression models. Various new properties of optimal designs with respect to the popular T-optimality criterion are derived, which in many circumstances allow an explicit determination of T-optimal designs. It is also demonstrated, that in nested linear models the number of support points of T-optimal designs is usually too small to estimate all parameters in the extended model. In many cases T-optimal designs are usually not unique, and in this situation we give a characterization of all T-optimal designs. Finally, T-optimal designs are compared with optimal discriminating designs with respect to alternative criteria by means of a small simulation study.

Keywords

41A50, 62K05, D_s-optimality, model discrimination, nonlinear approximation, optimal design, T-optimality

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