Continuous optimal designs for generalised linear models under model uncertainty
Woods, David C. and Lewis, Susan M. (2008) Continuous optimal designs for generalised linear models under model uncertainty. (M08/06). (Submitted).
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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.
|Keywords:||exponential family; general equivalence theorem; logistic regression; nonlinear regression; optimal design.|
|Subjects:||H Social Sciences > HA Statistics
Q Science > QA Mathematics
|Divisions:||University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute
|Date Deposited:||03 Oct 2008|
|Last Modified:||28 Mar 2014 15:19|
PLATFORM: End-to-End pipeline for chemical information: from the laboratory to literature and back again
Funded by: EPSRC (EP/C008863/1)
April 2005 to June 2010
|Publisher:||Southampton Statistical Sciences Research Institute|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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