Dette, HolgerTitoff, Stefanie2008-11-262008-11-262008-11-26http://hdl.handle.net/2003/2586910.17877/DE290R-1953We 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 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. AMS: 62K05enDs-optimalityModel discriminationNonlinear approximationOptimal designT-optimality004report