Multiple comparison procedures
Multiple comparison procedures
Sufficient conditions for functional-limit-theorem versions of L=λW
Queueing Systems: Theory and Applications
Management Science
Simulation run length planning
WSC '89 Proceedings of the 21st conference on Winter simulation
Ranking, selection and multiple comparisons in computer simulations
WSC '94 Proceedings of the 26th conference on Winter simulation
Two-stage stopping procedures based on standardized time series
Management Science
Two-stage procedures for multiple comparisons with a control in steady-state simulations
WSC '96 Proceedings of the 28th 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
Two-stage procedures for multiple comparisons with a control in steady-state simulations
WSC '96 Proceedings of the 28th conference on Winter simulation
A survey of ranking, selection, and multiple comparison procedures for discrete-event simulation
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Simulation optimization: a survey of simulation optimization techniques and procedures
Proceedings of the 32nd conference on Winter simulation
Ranking and selection for steady-state simulation
Proceedings of the 32nd conference on Winter simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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Suppose that we have k different stochastic systems, where /spl mu/i denotes the steady-state mean of system i. We assume that the system labeled k is a control and want to compare the performance of the other sys tems, labeled 1,2,...,k - 1, relative to this control. This problem is known in the statistical literature as multiple comparisons with a control (MCC). Independent steady-state simulations will be performed to compare the systems to the control. Two-stage procedures, based on the method of batch means, are presented to construct simultaneous lower one sided confidence intervals for/spl mu/i - /spl mu/k (i = 1, 2, . . ., k), each having prespecified (absolute or relative) half width 6. Under the assumption that the stochastic processes representing the evolution of the systems satisfy a functional central limit theorem, it can be shown that asymptotically (as /spl delta/ /spl rarr/ 0 with the size of the batches proportional to 1//spl delta//sup 2/), the joint probability that the confidence intervals simultaneously contain the /spl mu/i - /spl mu/k (i = 1, 2,..., k - 1) is at least 1 - /spl alpha/, where /spl alpha/ is prespecified by the user.