A REPLICATION APPROACH TO INTERVAL ESTIMATION IN SIMULATION

The authors modify an earlier approach developed for reducing the bias of the estimator for the mean response in simulation caused by the initial conditions. They try to balance the bias of the estimator in a simulation run by imposing a bias in the opposite direction in a companion run by suitably setting its initial conditions. They present analytical results for the bias of the estimator for AR(1) and M/M/s processes. They suggest making independent replications of the pairs of runs to construct a confidence interval for the mean response. They present some empirical results on the coverages and precisions of the confidence intervals. The results suggest that the idea of balancing a bias with a bias in the opposite direction is promising