Selection procedures with standardized time series variance estimators

Studies a modification of Y. Rinott´s (1978) two-stage procedure for selecting the normal population with the largest (or smallest) mean. The modification, which is appropriate for use in the simulation environment, uses, in the procedure´s first stage, different variance estimators than the usual batch means (BM) variance estimator. In particular, we use variance estimators arising from the method of standardized time series (STS). On the plus side, certain STS estimators have more degrees of freedom than the BM estimator does. On the other hand, STS variance estimators tend to require larger sample sizes than the BM estimator in order to converge to their assumed distributions. These considerations result in trade-offs involving the procedure´s achieved probability of correct selection as well as the procedure´s expected sample size