Article ID: | iaor20022570 |
Country: | United States |
Volume: | 33 |
Issue: | 3 |
Start Page Number: | 149 |
End Page Number: | 166 |
Publication Date: | Mar 2001 |
Journal: | IIE Transactions |
Authors: | Nelson Barry L., Banerjee Souvik |
Keywords: | simulation: analysis, statistics: inference |
We present two-stage experiment designs for use in simulation experiments that compare systems in terms of their expected (long-run average) performance. These procedures simultaneously achieve the following with a prespecified probability of being correct: (i) find the best system or a near-best system; (ii) identify a subset of systems that are more than a practically insignificant difference from the best; and (iii) provide a lower confidence bound on the probability that the best or near-best system will be selected. All of the procedures assume normally distributed data, but versions allow unequal variances and common random numbers.