Probability-based optimal design

McGree, J. M. and Eccleston, J. A. (2008) Probability-based optimal design. Australian and New Zealand Journal of Statistics, 50 1: 13-28. doi:10.1111/j.1467-842X.2007.00497.x

Author McGree, J. M.
Eccleston, J. A.
Title Probability-based optimal design
Journal name Australian and New Zealand Journal of Statistics   Check publisher's open access policy
ISSN 1369-1473
Publication date 2008-01-01
Sub-type Article (original research)
DOI 10.1111/j.1467-842X.2007.00497.x
Open Access Status
Volume 50
Issue 1
Start page 13
End page 28
Total pages 16
Editor K. Mengersen
Place of publication Australia
Publisher Blackwell Publishing Asia Pty Ltd.
Language eng
Subject C1
970101 Expanding Knowledge in the Mathematical Sciences
010405 Statistical Theory
Abstract Optimal design of experiments has generally concentrated on parameter estimation and, to a much lesser degree, on model discrimination. Often an experimenter is interested in a particular outcome and wishes to maximize in some way the probability of this outcome.We propose a new class of compound criteria and designs that address this issue for generalized linear models. The criteria offer a method of achieving designs that possess the properties of efficient parameter estimation and a high probability of a desired outcome.
Keyword compound criteria
generalized linear models
maximizing probability
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: 2009 Higher Education Research Data Collection
School of Mathematics and Physics
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Citation counts: TR Web of Science Citation Count  Cited 9 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 9 times in Scopus Article | Citations
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Created: Tue, 24 Mar 2009, 22:13:33 EST by Marie Grove on behalf of School of Mathematics & Physics