The University of Southampton
University of Southampton Institutional Repository

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), pp. 449-458. (doi:10.1093/biomet/asr001).

Record type: Article


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.

PDF s3ri-workingpaper-M10-02.pdf - Other
Download (283kB)

More information

Published date: June 2011
Keywords: additive model, bayesian d-optimality, partially nonlinear model, product design, q-optimality, standardised maximin d-optimality
Organisations: Statistics


Local EPrints ID: 144481
ISSN: 0006-3444
PURE UUID: 6530d9d4-2406-46f5-9411-f46c783aae38

Catalogue record

Date deposited: 14 Apr 2010 14:49
Last modified: 18 Jul 2017 23:08

Export record



Author: S. Biedermann
Author: H. Dette
Author: D.C. Woods

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.