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MAKING SIMULATIONS MORE EFFICIENT WHEN ANALYZING POISSON ARRIVAL SYSTEMS AND MEANS OF MONOTONE FUNCTIONS

Published online by Cambridge University Press:  06 March 2006

Sheldon M. Ross
Sheldon M. Ross
Affiliation:
Epstein Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, CA 90089-0193, [email protected]
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Abstract

For a system in which arrivals occur according to a Poisson process, we give a new approach for using simulation to estimate the expected value of a random variable that is independent of the arrival process after some specified time t. We also give a new approach for using simulation to estimate the expected value of an increasing function of independent uniform random variables. Stratified sampling is a key technique in both cases.

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 20 , Issue 2 , April 2006 , pp. 251 - 256
Copyright
© 2006 Cambridge University Press

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References

REFERENCES

Glasserman, P. (2004). Monte Carlo methods in financial engineering. New York: Springer.
Ross, S.M. (2002). Probability models for computer science. New York: Academic Press.
Ross, S.M. (2002). Simulation. New York: Academic Press.