Some optimal simulation designs for estimating quadratic response surface functions

Presents some experimental design strategies for simulation studies involving the estimation of quadratic response surfaces. Optimal design plans are developed in four common second-order design classes (central composite, Box-Behnken, three-level factorial, and small composite designs) using a criterion which incorporates both the bias and variance of the predicted response variable. Three methods of assigning pseudorandom number streams to design points are considered: independent streams, common streams, and the simultaneous use of common and antithetic streams in an orthogonally blockable experimental design. Each method uses independent streams for replications of design points. The findings indicate that carefully planned experimental designs can substantially improve the estimation of quadratic response surface models