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
It is a far, far better mean I find…
Proceedings of the 29th 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)
Selecting the best stochastic system for large scale problems in DEDS
Mathematics and Computers in 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
ADAPT Selection procedures to process correlated and non-normal data with batch means
Winter Simulation Conference
Hi-index | 0.00 |
Suppose that we want to compare k different systems, where /spl mu//sub i/ denotes the steady state mean performance of system i. Our goal is to use simulation to pick the "best" system (i.e., the one with the largest or smallest steady state mean). To do this, we present some two stage procedures based on the method of batch means. Our procedures also construct multiple comparisons with the best (MCB) confidence intervals for /spl mu//sub i/-max/sub j/spl ne/i//spl mu//sub j/, i=1,...,k. Under the assumption of an indifference zone of (absolute or relative) width /spl delta/, we can show that asymptotically (as /spl delta//spl rarr/0 with the size of the batches proportional to 1//spl delta//sup 2/), the joint probability of correctly selecting the best system and of the MCB confidence intervals simultaneously containing /spl mu//sub i/-max/sub j/spl ne/i//spl mu//sub j/, i=1,...,k, is at least 1-/spl alpha/, where /spl alpha/ is prespecified by the user.