Matrix analysis
A guide to simulation (2nd ed.)
A guide to simulation (2nd ed.)
Operations Research
Integrated variance reduction strategies
WSC '93 Proceedings of the 25th conference on Winter simulation
Combined correlation induction strategies for designed simulation experiments
WSC '93 Proceedings of the 25th conference on Winter simulation
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Antithetic variates and control variates are two well-known variance reduction techniques. We consider combining antithetic variates and control variates to estimate the mean response in a stochastic simulation experiment. When applying antithetic variates to generate control variates across paired replications, we show that the integrated control-variate estimator is unbiased and yields, under the assumption of common correlations induced for all control variates, a smaller variance than the conventional control-variate estimator without using antithetic variates. We examine the proposed estimator and two alternative integrated control-variate estimators when applying antithetic variates on control variates and show that the proposed estimator is the optimal integrated control-variate estimator We implement these three integrated control-variate estimators and the conventional control-variate estimator in a simulation model of a stochastic network to evaluate the performance of each control-variate estimator Empirical results show that the proposed estimator outperforms the other control-variate estimators.