Statistical fitting and validation of non-linear simulation metamodels: A case study

Linear regression metamodels have been widely used to explain the behavior of computer simulation models, although they do not always provide a good global fit to smooth response functions of arbitrary shape. In the case study discussed in this paper, the use of several linear regression polynomial results in a poor fit. The use of a non-linear regression metamodeling methodology provides simple functions that adequately approximate the behavior of the target simulation model. The importance of metamodel validation is emphasized by using the generalization of Rao s test to non-linear metamodels and double cross-validation. 2004 Published by Elsevier B.V.