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Continuous optimal designs for generalised linear models under model uncertainty

Record type: Article

We propose a general design selection criterion for experiments where a generalised linear model describes the response. The criterion allows for several competing aims, such as parameter estimation and model discrimination, and also for uncertainty in the functional form of the linear predictor, the link function and the unknown model parameters. A general equivalence theorem is developed for this criterion. In practice, an exact design is required by experimenters and can be obtained by numerical rounding of a continuous design. We derive bounds on the performance of an exact design under this criterion which allow the efficiency of a rounded continuous design to be assessed.

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Citation

Woods, David C. and Lewis, Susan M. (2008) Continuous optimal designs for generalised linear models under model uncertainty Journal of Statistical Theory and Practice

More information

Submitted date: 2 October 2008
Keywords: exponential family, general equivalence theorem, logistic regression, nonlinear regression, optimal design.

Identifiers

Local EPrints ID: 63323
URI: http://eprints.soton.ac.uk/id/eprint/63323
ISSN: 1559-8608
PURE UUID: 9fec3f03-1bca-43a4-9978-b7ea4cb74eee

Catalogue record

Date deposited: 03 Oct 2008
Last modified: 17 Jul 2017 14:18

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