| Article ID: | iaor19951140 |
| Country: | Switzerland |
| Volume: | 53 |
| Issue: | 1 |
| Start Page Number: | 175 |
| End Page Number: | 197 |
| Publication Date: | Nov 1994 |
| Journal: | Annals of Operations Research |
| Authors: | Glynn Peter W. |
| Keywords: | variance reduction |
This paper provides an overview of the five most commonly used statistical techniques for improving the efficiency of stochastic simulations: control variates, common random numbers, importance sampling, conditional Monte Carlo, and stratification. The paper also describes a mathematical framework for discussion of efficiency issues that quantifies the trade-off between lower variance and higher computational time per observation.