A comprehensive review of methods for simulation output analysis
Proceedings of the 38th conference on Winter simulation
Experimental evaluation of integrated path estimators
Proceedings of the 38th conference on Winter simulation
Simulation output analysis using integrated paths
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Fortieth anniversary special panel: Landmark papers
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Fortieth anniversary special panel: Landmark papers
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Statistical analysis of simulation output: state of the art
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Low bias integrated path estimators
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Folded standardized time series area variance estimators for simulation
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Ranking and selection techniques with overlapping variance estimators
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
A distribution-free tabular CUSUM chart for correlated data with automated variance estimation
Proceedings of the 40th Conference on Winter Simulation
Simulation output analysis using integrated paths II: Low bias estimators
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Performance of folded variance estimators for simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Linear combinations of overlapping variance estimators for simulation
Operations Research Letters
A new perspective on batched quantile estimation
Proceedings of the Winter Simulation Conference
Thirty years of "batch size effects"
Proceedings of the Winter Simulation Conference
Overlapping batch means: something more for nothing?
Proceedings of the Winter Simulation Conference
Overlapping batches for the assessment of solution quality in stochastic programs
Proceedings of the Winter Simulation Conference
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For a steady-state simulation output process, we formulate efficient algorithms to compute certain estimators of the process variance parameter (i.e., the sum of covariances at all lags), where the estimators are derived in principle from overlapping batches separately and then averaged over all such batches. The algorithms require order-of-sample-size work to evaluate overlapping versions of the area and Cramér--von Mises estimators arising in the method of standardized time series. Recently, Alexopoulos et al. showed that, compared with estimators based on nonoverlapping batches, the estimators based on overlapping batches achieve reduced variance while maintaining similar bias asymptotically as the batch size increases. We provide illustrative analytical and Monte Carlo results for M/M/1 queue waiting times and for a first-order autoregressive process. We also present evidence that the asymptotic distribution of each overlapping variance estimator can be closely approximated using an appropriately rescaled chi-squared random variable with matching mean and variance.