Optimal design for additive partially nonlinear models
Biedermann, S., Dette, H. and Woods, D.C. (2011) Optimal design for additive partially nonlinear models. Biometrika, 98, (2), 449-458. (doi:10.1093/biomet/asr001).
We develop optimal design theory for additive partially nonlinear regression models, showing that Bayesian and standardized maximin D-optimal designs can be found as the products of the corresponding optimal designs in one dimension. A sufficient condition under which analogous results hold for Ds-optimality is derived to accommodate situations in which only a subset of the model parameters is of interest. To facilitate prediction of the response at unobserved locations, we prove similar results for Q-optimality in the class of all product designs. The usefulness of this approach is demonstrated through an application from the automotive industry, where optimal designs for least squares regression splines are determined and compared with designs commonly used in practice.
|Keywords:||additive model, bayesian d-optimality, partially nonlinear model, product design, q-optimality, standardised maximin d-optimality|
|Subjects:||H Social Sciences > HA Statistics|
|Divisions:||University Structure - Pre August 2011 > School of Mathematics > Statistics
|Date Deposited:||14 Apr 2010 14:49|
|Last Modified:||15 Mar 2012 16:43|
|Contributors:||Biedermann, S. (Author)
Dette, H. (Author)
Woods, D.C. (Author)
|Publisher:||Southampton Statistical Sciences Research Institute, University of Southampton|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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