The University of Southampton
University of Southampton Institutional Repository

Optimal designs for multivariable spline models

Optimal designs for multivariable spline models
Optimal designs for multivariable spline models
In this paper, we investigate optimal designs for multivariate additive spline regression
models. We assume that the knot locations are unknown, so must be estimated from the
data. In this situation, the Fisher information for the full parameter vector depends on the
unknown knot locations, resulting in a non-linear design problem. We show that locally,
Bayesian and maximin D-optimal designs can be found as the products of the optimal
designs in one dimension. A similar result is proven for Q-optimality in the class of all
product designs
M09/16
Southampton Statistical Sciences Research Institute, University of Southampton
Biedermann, Stefanie
fe3027d2-13c3-4d9a-bfef-bcc7c6415039
Dette, Holger
8c7b1c2e-3adc-45df-acfc-9e76509a228e
Woods, David C.
ae21f7e2-29d9-4f55-98a2-639c5e44c79c
Biedermann, Stefanie
fe3027d2-13c3-4d9a-bfef-bcc7c6415039
Dette, Holger
8c7b1c2e-3adc-45df-acfc-9e76509a228e
Woods, David C.
ae21f7e2-29d9-4f55-98a2-639c5e44c79c

Biedermann, Stefanie, Dette, Holger and Woods, David C. (2009) Optimal designs for multivariable spline models (S3RI Methodology Working Papers, M09/16) Southampton, UK. Southampton Statistical Sciences Research Institute, University of Southampton 28pp.

Record type: Monograph (Working Paper)

Abstract

In this paper, we investigate optimal designs for multivariate additive spline regression
models. We assume that the knot locations are unknown, so must be estimated from the
data. In this situation, the Fisher information for the full parameter vector depends on the
unknown knot locations, resulting in a non-linear design problem. We show that locally,
Bayesian and maximin D-optimal designs can be found as the products of the optimal
designs in one dimension. A similar result is proven for Q-optimality in the class of all
product designs

Text
s3ri-workingpaper-M09-16.pdf - Other
Download (577kB)

More information

Published date: 30 September 2009

Identifiers

Local EPrints ID: 69157
URI: http://eprints.soton.ac.uk/id/eprint/69157
PURE UUID: 50f63312-b91c-4829-90f4-76ef51e33cfe
ORCID for Stefanie Biedermann: ORCID iD orcid.org/0000-0001-8900-8268
ORCID for David C. Woods: ORCID iD orcid.org/0000-0001-7648-429X

Catalogue record

Date deposited: 22 Oct 2009
Last modified: 14 Mar 2024 02:51

Export record

Contributors

Author: Holger Dette
Author: David C. Woods ORCID iD

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.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

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.

×