The problem of constructing optimal designs for a class of regression models is considered. We investigate a version of the Tp-optimality criterion as introduced by Atkinson and Fedorov (1975b) and demonstrate that optimal designs with respect to this type of criteria can be obtained by solving (nonlinear) vector-valued approximation problems. We provide a characterization of the best approximations in this context and use these results to develop an efficient algorithm for the determination of the optimal discriminating designs. The results are illustrated by fnumerical examples.
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