A mean squared error criterion for the design of experiments

Abstract

In estimating a response surface over a design region of interest, mean squared error can arise both from sampling variance and bias introduced by model inadequacy. The criterion adopted here for experimental design attempts to protect against bias resulting from a large class of deviations from the assumed model. Two algorithms are proposed for the construction of either approximate or exact designs and an example is given.