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Optimal discrimination designs for exponential regression models

Biedermann, Stefanie, Dette, Holger and Pepelyshev, Andrey (2007) Optimal discrimination designs for exponential regression models Journal of Statistical Planning and Inference, 137, (8), pp. 2579-2592. (doi:10.1016/j.jspi.2006.03.015).

Record type: Article


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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Published date: 2007
Keywords: compartmental model, model discrimination, discrimination design, locally optimal design, robust optimal design, maximin optimal design
Organisations: Statistics


Local EPrints ID: 58645
ISSN: 0378-3758
PURE UUID: 6d01a34f-a5c3-4c6a-a4f6-585a093785d0

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Date deposited: 19 Aug 2008
Last modified: 17 Jul 2017 14:26

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Author: Holger Dette
Author: Andrey Pepelyshev

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