Efficient experimental designs for sigmoidal growth models

Dette, H. and Pepelyshev, Andrey ORCID: https://orcid.org/0000-0001-5634-5559 2008. Efficient experimental designs for sigmoidal growth models. Journal of Statistical Planning and Inference 138 (1) , pp. 2-17. 10.1016/j.jspi.2007.05.027

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Abstract

For the Weibull- and Richards-regression model robust designs are determined by maximizing a minimum of D- or D1-efficiencies, taken over a certain range of the non-linear parameters. It is demonstrated that the derived designs yield a satisfactory solution of the optimal design problem for this type of model in the sense that these designs are efficient and robust with respect to misspecification of the unknown parameters. Moreover, the designs can also be used for testing the postulated form of the regression model against a simplified sub-model.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Mathematics
Subjects:	Q Science > QA Mathematics
Uncontrolled Keywords:	Sigmoidal growth; Weibull regression model; Exponential regression model; Richards-regression model; Logistic regression model; Robust optimal design; Goodness-of-fit test
Publisher:	Elsevier
ISSN:	03783758
Last Modified:	24 Oct 2022 11:42
URI:	https://orca.cardiff.ac.uk/id/eprint/49057

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