Robust prediction and extrapolation designs for nonlinear regression with imprecision

摘要

We consider the general situation of fitting an assumed nonlinear regression model which is possibly misspecified. The minimax designs for both response prediction and extrapolation in biased nonlinear regression models are discussed. We extend previous work of others from linear response or a given function of linear response to intrinsically nonlinear response. Several examples are illustrated such as designing for a yield-fertilizer model, a simple compartmental model, and a Michaelis-Menten model.