Fundamentals of queueing theory (2nd ed.).
Fundamentals of queueing theory (2nd ed.).
Sufficient conditions for functional-limit-theorem versions of L=λW
Queueing Systems: Theory and Applications
Management Science
Properties of standardized time series weighted area variance estimators
Management Science
Simulation output analysis using standardized time series
Mathematics of Operations Research
Multiple comparisons with the best for steady-state simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Two-stage stopping procedures based on standardized time series
Management Science
Standardized Time Series LP-Norm Variance Estimators for Simulations
Management Science
Batch-size effects on simulation optimization using multiple comparisons with the best
WSC' 90 Proceedings of the 22nd conference on Winter simulation
A fully sequential procedure for indifference-zone selection in simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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
Statistical analysis of simulation output: output data analysis for simulations
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Review of advanced methods for simulation output analysis
WSC '05 Proceedings of the 37th conference on Winter simulation
Selection and multiple-comparison procedures for regenerative systems
Proceedings of the 38th conference on Winter simulation
Recent advances in ranking and selection
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Single-stage multiple-comparison procedure for quantiles and other parameters
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Proceedings of the 40th Conference on Winter Simulation
Thirty years of "batch size effects"
Proceedings of the Winter Simulation Conference
| Hi-index | 0.00 |
Procedures for multiple comparisons with the best are investigated in the context of steady-state simulation, whereby a number k of different systems (stochastic processes) are compared based upon their (asymptotic) means &mgr;i (i = 1,2,…, k). The variances of these (asymptotically stationary) processes are assumed to be unknown and possibly unequal. We consider the problem of constructing simultaneous confidence intervals for mi-max j≠imj i=1,2,&ldots;,k which is known as multiple comparisons with the best (MCB). Our intervals are constrained to contain 0, and so are called constrained MCB intervals. In particular, two-stage procedures for construction of absolute- and relative-width confidence intervals are presented. Their validity is addressed by showing that the confidence intervals cover the parameters with probability of at least some user-specified threshold value, as the confidence intervals' width parameter shrinks to 0. The general assumption about the processes is that they satisfy a functional central limit theorem. The simulation output analysis procedures are based on the method of standardized time series (the batch means method is a special case). The techniques developed here extend to other multiple-comparison procedures such as unconstrained MCB, multiple comparisons with a control, and all-pairwise comparisons. Although simulation is the context in this paper, the results naturally apply to (asymptotically) stationary time series.