The University of Southampton
University of Southampton Institutional Repository

Constrained optimal discrimination designs for Fourier regression models

Biedermann, Stefanie, Dette, Holger and Hoffmann, Philipp (2009) Constrained optimal discrimination designs for Fourier regression models Annals of the Institute of Statistical Mathematics, 61, (1), pp. 143-157. (doi:10.1007/s10463-007-0133-5).

Record type: Article

Abstract

In this article, the problem of constructing efficient discrimination designs in a Fourier regression model is considered. We propose designs which maximize the power of the F-test,
which discriminates between the two highest order models, subject to the constraints that the tests that discriminate between lower order models have at least some given
relative power. A complete solution is presented in terms of the canonical moments of the optimal designs, and for the special case of equal constraints even more specific formulae
are available

PDF revision_2(short).pdf - Other
Restricted to Repository staff only
Download (162kB)

More information

Published date: March 2009
Keywords: constrained optimal designs, trigonometric regression, d1-optimal designs, chebyshev polynomials, canonical moments
Organisations: Southampton Statistical Research Inst.

Identifiers

Local EPrints ID: 79815
URI: http://eprints.soton.ac.uk/id/eprint/79815
ISSN: 0020-3157
PURE UUID: e2f3a087-c700-4c6d-bfc9-16dc7deb0b77

Catalogue record

Date deposited: 22 Mar 2010
Last modified: 18 Jul 2017 23:16

Export record

Altmetrics

Contributors

Author: Holger Dette
Author: Philipp Hoffmann

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.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.

×