Optimal discrimination designs
By Holger Dette, S. Titoff. 2009
75 citations recorded by the source corpus.
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 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.
Subfields: Computational Theory and Mathematics, Industrial and Manufacturing Engineering, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/e82f57cc91e183d1ceed48c233ee9a8be74b956a
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In Computational Theory and Mathematics
In Industrial and Manufacturing Engineering
In Management Science and Operations Research
Citations in the corpus
- Robust discrimination designs (2009, background): “In this framework Dette and Titoff (2008) linked the T -optimality problem to a problem of optimal non-linear approximation and went on to obtain results on the number of support points required.”