A pseudo-random number assignment strategy for the estimation of quadratic metamodels

Whereas an optimal Pseudo-Random Number (PRN) assignment strategy for simulation experiments involving the estimation of linear metamodels currently exists, no such optimal assignment strategy for quadratic metamodels has been proposed. This situation is now rectified by the introduction of a PRN assignment strategy for a quadratic metamodel for 3 ^k factorial designs. In addition to extending the theory from linear to quadratic metamodels, the proposed PRN strategy is shown to be superior to a number of existing and competing strategies in terms of various variance measures.