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Asymptotic Properties of Some Confidence Interval Estimators for Simulation Output

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Author Info

  • David Goldsman

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Lee Schruben

    (School of OR & IE, Cornell University, Ithaca, New York 14853)

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    Abstract

    The classical confidence interval estimator commonly used in simulation is compared with four new estimators based on standardization of a time series presented in a previous paper. These new interval estimators are shown to have asymptotic properties that strictly dominate the classical estimator when used with data from independent simulation replications or means of batched observations from a single simulation run. Two of the new estimators also can be used with a single unbatched replication of a simulation program, a situation where the classical estimator is not defined.

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    File URL: http://dx.doi.org/10.1287/mnsc.30.10.1217
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 30 (1984)
    Issue (Month): 10 (October)
    Pages: 1217-1225

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    Handle: RePEc:inm:ormnsc:v:30:y:1984:i:10:p:1217-1225

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    Related research

    Keywords: simulation; statistical analysis; time series;

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    Cited by:
    1. Kevork, Ilias S., 2010. "Estimating the optimal order quantity and the maximum expected profit for single-period inventory decisions," Omega, Elsevier, vol. 38(3-4), pages 218-227, June.
    2. Song, Wheyming Tina, 1996. "On the estimation of optimal batch sizes in the analysis of simulation output," European Journal of Operational Research, Elsevier, vol. 88(2), pages 304-319, January.

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