Optimal and efficient designs for Gompertz regression models

Gang Li ()

Annals of the Institute of Statistical Mathematics, 2012, vol. 64, issue 5, 945-957

Abstract: Gompertz functions have been widely used in characterizing biological growth curves. In this paper we consider D-optimal designs for Gompertz regression models. For homoscedastic Gompertz regression models with two or three parameters, we prove that D-optimal designs are minimally supported. Considering that minimally supported designs might not be applicable in practice, alternative designs are proposed. Using the D-optimal designs as benchmark designs, these alternative designs are found to be efficient in general. Copyright The Institute of Statistical Mathematics, Tokyo 2012

Keywords: D-optimality; Local optimality; Minimally supported designs; Sigmoid growth curve; Tchebycheff system (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/s10463-011-0340-y

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