Woods, David C. and Lewis, Susan M.
Continuous optimal designs for generalised linear models under model uncertainty
Journal of Statistical Theory and Practice
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.
||exponential family, general equivalence theorem, logistic regression, nonlinear regression, optimal design.
|2 October 2008||Submitted|
||03 Oct 2008
||16 Apr 2017 17:26
|Further Information:||Google Scholar|
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