Efficient geometric and uniform design strategies for sigmoidal regression models
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 th...
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th-cmuir.6653943832-58502014-08-30T03:23:32Z Efficient geometric and uniform design strategies for sigmoidal regression models O'Brien T.E. Chooprateep S. Homkham N. 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. 2014-08-30T03:23:32Z 2014-08-30T03:23:32Z 2009 Article 0038271X http://www.scopus.com/inward/record.url?eid=2-s2.0-67650136138&partnerID=40&md5=507f95c1657f3d1bdfcea8776877eec7 http://cmuir.cmu.ac.th/handle/6653943832/5850 English |
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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. |
| format |
Article |
| author |
O'Brien T.E. Chooprateep S. Homkham N. |
| spellingShingle |
O'Brien T.E. Chooprateep S. Homkham N. Efficient geometric and uniform design strategies for sigmoidal regression models |
| author_facet |
O'Brien T.E. Chooprateep S. Homkham N. |
| author_sort |
O'Brien T.E. |
| title |
Efficient geometric and uniform design strategies for sigmoidal regression models |
| title_short |
Efficient geometric and uniform design strategies for sigmoidal regression models |
| title_full |
Efficient geometric and uniform design strategies for sigmoidal regression models |
| title_fullStr |
Efficient geometric and uniform design strategies for sigmoidal regression models |
| title_full_unstemmed |
Efficient geometric and uniform design strategies for sigmoidal regression models |
| title_sort |
efficient geometric and uniform design strategies for sigmoidal regression models |
| publishDate |
2014 |
| url |
http://www.scopus.com/inward/record.url?eid=2-s2.0-67650136138&partnerID=40&md5=507f95c1657f3d1bdfcea8776877eec7 http://cmuir.cmu.ac.th/handle/6653943832/5850 |
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