Sacks, Jerome; Schiller, Susannah B.; Welch, William J. (1989, ASQC and the American Statistical Association) University of Illinois, Champaign, IL; University of Waterloo, Canada
A computer experiment generates observations by running a computer model at inputs x and recording the output (response) Y. Prediction of the response Y to an untried input is treated by modeling the systematic departure of Y from a linear model as a realization of a stochastic process. For given data (selected inputs and the computed responses), best linear prediction is used. The design problem is to select the inputs to predict efficiently. The issues of choice of stochastic-process model and computation of efficient designs are addressed, and applications are made to some chemical kinetics problems.
Computer-Aided Design (CAD),Prediction,Response surfaces,Correlation,Computers