Nonminimally supported design for three parameters generalized exponential model

Abstract

The exponential models are widely applied in several fields as a growth curve. The D-optimal design is a minimally supported design, the number of supported designs is the same as the number of parameters with uniform weight. Nonminimally supported design is a design with the number of supported designs is greater than the number of parameters. In this paper, we investigated nonminimally supported design that is built using four supported points with uniform weight and determination of the supported designs by maximizing the determinant of information matrix. Determination of the supported designs use two ways, first by deriving the objective function formula, which is  determinant of the information matrix then maximized it, second by adding one supported point to the minimally supported design. Based on the numerical simulation of two methods, nonminimally supported design with the maximum determinant value is the best nonminimally supported design.