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June 1996 A note on Bayesian c- and D-optimal designs in nonlinear regression models
Holger Dette
Ann. Statist. 24(3): 1225-1234 (June 1996). DOI: 10.1214/aos/1032526965

Abstract

We present a version of Elfving's theorem for the Bayesian D-optimality criterion in nonlinear regression models. The Bayesian optimal design can be characterized as a design which allows a representation of a (uniquely determined) boundary point of a convex subset of $L^2$-integrable functions. A similar characterization is given for the Bayesian c-optimality criterion where a (possible) nonlinear function of the unknown parameters has to be estimated. The results are illustrated in the example of an exponential growth model using a gamma prior distribution.

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Holger Dette. "A note on Bayesian c- and D-optimal designs in nonlinear regression models." Ann. Statist. 24 (3) 1225 - 1234, June 1996. https://doi.org/10.1214/aos/1032526965

Information

Published: June 1996
First available in Project Euclid: 20 September 2002

zbMATH: 0866.62046
MathSciNet: MR1401846
Digital Object Identifier: 10.1214/aos/1032526965

Subjects:
Primary: 62K05

Rights: Copyright © 1996 Institute of Mathematical Statistics

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Vol.24 • No. 3 • June 1996
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