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).

This is the latest version of this item.


[img] PDF revision_2(short).pdf - Other
Restricted to Repository staff only

Download (162kB)


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

Item Type: Article
Digital Object Identifier (DOI): doi:10.1007/s10463-007-0133-5
ISSNs: 0020-3157 (print)
Keywords: constrained optimal designs, trigonometric regression, d1-optimal designs, chebyshev polynomials, canonical moments
ePrint ID: 79815
Date :
Date Event
March 2009Published
Date Deposited: 22 Mar 2010
Last Modified: 18 Apr 2017 20:13
Further Information:Google Scholar

Available Versions of this Item

Actions (login required)

View Item View Item