Information capacity designs for generalized linear models

Poster

Swan, Taryn, McGree, James, Lewis, Susan and Woods, Dave. 2010. "Information capacity designs for generalized linear models." Royal Statistical Society 2010 International Conference. Brighton, United Kingdom 13 - 17 Sep 2010
Paper/Presentation Title

Information capacity designs for generalized linear models

Presentation TypePoster
AuthorsSwan, Taryn (Author), McGree, James (Author), Lewis, Susan (Author) and Woods, Dave (Author)
Number of Pages1
Year2010
Web Address (URL) of Paperhttps://rss.conference-services.net/reports/template/onetextabstract.xml?xsl=template/onetextabstract.xsl&conferenceID=2133&abstractID=413798
Conference/EventRoyal Statistical Society 2010 International Conference
Event Details
Royal Statistical Society 2010 International Conference
Event Date
13 to end of 17 Sep 2010
Event Location
Brighton, United Kingdom
Abstract

Information Capacity (IC) is a criterion for selecting a design for an experiment based on its effectiveness in estimating a set of models to be investigated in the data analysis (Li and Nachtsheim (2000)). This presentation will describe how this criterion can be applied to experiments where a generalized linear model (GLM) describes the measured response. Three different types of IC designs will be compared with the aim of achieving accurate estimation of the models in the set and discriminating between the competing models. Recent work on experiments for both estimation and discrimination in nonlinear models, includes Waterhouse et al. (2009).

ANZSRC Field of Research 2020490501. Applied statistics
Public Notes

Poster presentation.

Byline AffiliationsUniversity of Queensland
Queensland University of Technology
University of Southampton, United Kingdom
Institution of OriginUniversity of Southern Queensland
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