Article ID: | iaor20052387 |
Country: | Netherlands |
Volume: | 156 |
Issue: | 2 |
Start Page Number: | 390 |
End Page Number: | 414 |
Publication Date: | Jul 2004 |
Journal: | European Journal of Operational Research |
Authors: | Nakayama Marvin K., Calvin James M. |
In a previous paper we introduced a new variance-reduction technique for regenerative simulations based on permuting regeneration cycles. In this paper we apply this idea to new classes of estimators. In particular, we derive permuted versions of likelihood-ratio derivative estimators for steady-state performance measures, importance-sampling estimators of the mean cumulative reward until hitting a set of states, and Tin estimators for steady-state ratio formulas. Empirical results are presented showing that modest to significant variance reductions can be obtained.