Parameter sensitivity of covariance-based response surfaces for modeling IC processes

When modeling the results of computer experiments which do not suffer from random errors, it is desirable that the models used exactly reproduce all the simulated data points. This paper discusses a method that ensures this and examines how small variations of the estimated parameters of the model influence the accuracy of the prediction. These findings are used to justify a procedure whereby the conditioning difficulties inherent in the method can be overcome.