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Bias Considerations in Simulation Experiments

Author

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  • George S. Fishman

    (Yale University, New Haven, Connecticut)

Abstract

This paper uses a first-order autoregressive scheme to investigate the effects of initial conditions in a simulation on the estimation of the population mean of a process of interest. The effects are measured by bias and variance. The results show that the elimination of observations near the beginning of the simulation reduces bias, as intended, but increases the variance, sometimes significantly.

Suggested Citation

  • George S. Fishman, 1972. "Bias Considerations in Simulation Experiments," Operations Research, INFORMS, vol. 20(4), pages 785-790, August.
    • Handle: RePEc:inm:oropre:v:20:y:1972:i:4:p:785-790
    DOI: 10.1287/opre.20.4.785
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    Cited by:

    1. Enver Yücesan, 1993. "Randomization tests for initialization bias in simulation output," Naval Research Logistics (NRL), John Wiley & Sons, vol. 40(5), pages 643-663, August.
    2. Crawford, J. W. & Gallwey, T. J., 2000. "Bias and variance reduction in computer simulation studies," European Journal of Operational Research, Elsevier, vol. 124(3), pages 571-590, August.
    3. Christos Alexopoulos & David Goldsman & Anup C. Mokashi & Kai-Wen Tien & James R. Wilson, 2019. "Sequest: A Sequential Procedure for Estimating Quantiles in Steady-State Simulations," Operations Research, INFORMS, vol. 67(4), pages 1162-1183, July.
    4. Sungmin Park & John W. Fowler & Gerald T. Mackulak & J. Bert Keats & W. Matthew Carlyle, 2002. "D-Optimal Sequential Experiments for Generating a Simulation-Based Cycle Time-Throughput Curve," Operations Research, INFORMS, vol. 50(6), pages 981-990, December.
    5. Sandikci, Burhaneddin & Sabuncuoglu, Ihsan, 2006. "Analysis of the behavior of the transient period in non-terminating simulations," European Journal of Operational Research, Elsevier, vol. 173(1), pages 252-267, August.

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