The Annals of Statistics

Optimal discrimination designs

Holger Dette and Stefanie Titoff

Full-text: Open access

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.

Article information

Source
Ann. Statist., Volume 37, Number 4 (2009), 2056-2082.

Dates
First available in Project Euclid: 18 June 2009

Permanent link to this document
https://projecteuclid.org/euclid.aos/1245332840

Digital Object Identifier
doi:10.1214/08-AOS635

Mathematical Reviews number (MathSciNet)
MR2533479

Zentralblatt MATH identifier
1168.62066

Subjects
Primary: 62K05: Optimal designs 41A50: Best approximation, Chebyshev systems

Keywords
Model discrimination optimal design T-optimality D_s-optimality nonlinear approximation

Citation

Dette, Holger; Titoff, Stefanie. Optimal discrimination designs. Ann. Statist. 37 (2009), no. 4, 2056--2082. doi:10.1214/08-AOS635. https://projecteuclid.org/euclid.aos/1245332840


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