Principles of Discrete Event Simulation
Principles of Discrete Event Simulation
Overlapping batch means: something for nothing?
WSC '84 Proceedings of the 16th conference on Winter simulation
Steady-state simulation of queueing processes: survey of problems and solutions
ACM Computing Surveys (CSUR)
Advanced output analysis for simulation
WSC '92 Proceedings of the 24th conference on Winter simulation
A review of advanced methods for simulation output analysis
WSC '94 Proceedings of the 26th conference on Winter simulation
Advanced methods for simulation output analysis
WSC '95 Proceedings of the 27th conference on Winter simulation
Batching methods in simulation output analysis: what we know and what we don't
WSC '96 Proceedings of the 28th conference on Winter simulation
Advanced simulation output analysis for a single system
WSC '93 Proceedings of the 25th conference on Winter simulation
Implementing the batch means method in simulation experiments
WSC '96 Proceedings of the 28th conference on Winter simulation
Computational efficiency of batching methods
Proceedings of the 29th conference on Winter simulation
Optimal quadratic-form estimator of the variance of the sample mean
Proceedings of the 29th conference on Winter simulation
Advanced methods for simulation output analysi8
Proceedings of the 30th conference on Winter simulation
Correlation among estimators of the variance of the sample mean
WSC '87 Proceedings of the 19th conference on Winter simulation
WSC' 90 Proceedings of the 22nd conference on Winter simulation
Output analysis: output analysis for simulations
Proceedings of the 32nd conference on Winter simulation
A perspective of batching methods in a simulation environment of multiple replications in parallel
Proceedings of the 32nd conference on Winter simulation
Output analysis: output data analysis for simulations
Proceedings of the 33nd conference on Winter simulation
On the MSE robustness of batching estimators
Proceedings of the 33nd conference on Winter simulation
On the MSE robustness of batching estimators
Proceedings of the 33nd conference on Winter simulation
Statistical analysis of simulation output: output data analysis for simulations
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Overlapping variance estimators for simulations
WSC '04 Proceedings of the 36th conference on Winter simulation
Review of advanced methods for simulation output analysis
WSC '05 Proceedings of the 37th conference on Winter simulation
Linear combinations of overlapping variance estimators for simulations
WSC '05 Proceedings of the 37th conference on Winter simulation
A comprehensive review of methods for simulation output analysis
Proceedings of the 38th conference on Winter simulation
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
Proceedings of the 40th Conference on Winter Simulation
Performance of folded variance estimators for simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
On the robustness of batching estimators
Operations Research Letters
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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The conventional method of batch means and the overlapping batch means approach of Meketon and Schmeiser are related to spectral estimation via the time averaging of subsequence periodograms. It is shown that most of the reduction in the variance of the variance estimate can be achieved with modest amounts of overlapping. This may have practical implications because of the large number of batches required for the statistical test of lack of correlation. and the usual practice of rebatching the data after this test is passed.