Optimal discrimination designs for exponential regression models
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Date
2005-07-29T09:23:40Z
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Abstract
We investigate optimal designs for discriminating between exponential regression models
of different complexity, which are widely used in the biological sciences; see, e.g.,
Landaw (1995) or Gibaldi and Perrier (1982). We discuss different approaches for the
construction of appropriate optimality criteria, and find sharper upper bounds on the
number of support points of locally optimal discrimination designs than those given by
Caratheodory’s Theorem. These results greatly facilitate the numerical construction of
optimal designs. Various examples of optimal designs are then presented and compared
to different other designs. Moreover, to protect the experiment against misspecifications
of the nonlinear model parameters, we adapt the design criteria such that the resulting
designs are robust with respect to such misspecifications and, again, provide several
examples, which demonstrate the advantages of our approach.
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Keywords
Compartmental model, Discrimination design, Locally optimal design, Maximin optimal design, Model discrimination, Robust optimal design