Autor(en): | Braess, Dietrich Dette, Holger |
Titel: | On the number of support points of maximin and Bayesian D-optimal designs in nonlinear regression models |
Sprache (ISO): | en |
Zusammenfassung: | We consider maximin and Bayesian D -optimal designs for nonlinear regression models. The maximin criterion requires the specification of a region for the nonlinear parameters in the model, while the Bayesian optimality criterion assumes that a prior distribution for these parameters is available. It was observed empirically by many authors that an increase of uncertainty in the prior information (i.e. a larger range for the parameter space in the maximin criterion or a larger variance of the prior distribution in the Bayesian criterion) yields a larger number of support points of the corresponding optimal designs. In this paper we present a rigorous proof of this phenomenon and show that in many nonlinear regression models the number of support points of Bayesian- and maximin D -optimal designs can become arbitrarily large if less prior information is available. Our results also explain why maximin D -optimal designs are usually supported at more different points than Bayesian D -optimal designs. |
URI: | http://hdl.handle.net/2003/20092 http://dx.doi.org/10.17877/DE290R-2766 |
Erscheinungsdatum: | 2004 |
Provinienz: | Universität Dortmund |
Enthalten in den Sammlungen: | Sonderforschungsbereich (SFB) 475 |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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78_04.pdf | DNB | 187.3 kB | Adobe PDF | Öffnen/Anzeigen |
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