A sequential procedure for estimating the steady-state mean using standardized time series

We propose SPSTS, an automated sequential procedure for computing point and confidence-interval (CI) estimators for the steady-state mean of a simulation output process. This procedure is based on variance estimators computed from standardized time series, and it is characterized by its simplicity relative to methods based on batch means and its ability to deliver CIs for the variance parameter of the output process. The effectiveness of SPSTS is evaluated via comparisons with methods based on batch means. In preliminary experimentation with the steady-state waiting-time process for the M/M/1 queue with a server utilization of 90%, we found that SPSTS performed comparatively well in terms of its average required sample size as well as the coverage and average half-length of its delivered CIs.