EFFICIENT DESIGNS FOR NONLINEAR MODELING

In the modeling of physical systems, such as chemical reactions, nonlinear models in a set of unknown parameters are commonly developed. Using the method of least squares for model fitting the efficiency of the process is measured by the large sample variance of the parameter estimates. Designs which yield desirable properties in the linear case, such as factorial and central composite designs, are often utilized in the nonlinear model setting. In this paper a method for transforming these standard designs, yielding more efficient estimators, in the nonlinear model case is proposed. The procedure is demonstrated on a typical kinetic reaction model.