Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/59519
Title: Efficient geometric and uniform design strategies for sigmoidal regression models
Authors: Timothy E. O'Brien
Suree Chooprateep
Nontiya Homkham
Authors: Timothy E. O'Brien
Suree Chooprateep
Nontiya Homkham
Keywords: Decision Sciences;Mathematics
Issue Date: 15-Jul-2009
Abstract: This paper provides practical guidelines for choosing efficient geometric and uniform designs for the logistic class of dose-response bioassay model functions in both the homoskedastic Gaussian and Binomial settings. The efficiencies of the designs provided here are typically above 90%, and since the number of design support points generally exceeds the number of parameters, these designs provide a useful and efficient means to confirm the assumed model. Extensions of our basic strategy include a Bayesian maxi-min design approach to reflect a range of values of the initial parameter estimates, as well as geometric/uniform design analogues when uncertainty exists as to the correct scale or to take account of curvature.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=67650136138&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/59519
ISSN: 0038271X
Appears in Collections:CMUL: Journal Articles

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