Permuted derivative and importance-sampling estimators for regenerative simulations

Permuted derivative and importance-sampling estimators for regenerative simulations

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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: ,
Abstract:

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.

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