Optimal discrimination designs

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. © Institute of Mathematical Statistics, 2009.