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A pooled percentile estimator for parallel simulations

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  • Qiong Zhang
  • Bo Wang
  • Wei Xie

Abstract

Percentile is an important risk measure quantifying the stochastic system random behaviours. This paper studies a pooled percentile estimator, which is the sample percentile of detailed simulation outputs after directly pooling independent sample paths together. We derive the asymptotic representation of the pooled percentile estimator and further prove its normality. By comparing with the classical percentile estimator used in stochastic simulation, both theoretical and empirical studies demonstrate the advantages of the proposal under the context of parallel simulation.

Suggested Citation

  • Qiong Zhang & Bo Wang & Wei Xie, 2022. "A pooled percentile estimator for parallel simulations," Journal of Simulation, Taylor & Francis Journals, vol. 16(1), pages 73-83, January.
    • Handle: RePEc:taf:tjsmxx:v:16:y:2022:i:1:p:73-83
    DOI: 10.1080/17477778.2020.1758597
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    Cited by:

    1. Xie, Wei & Barton, Russell R. & Nelson, Barry L. & Wang, Keqi, 2023. "Stochastic simulation uncertainty analysis to accelerate flexible biomanufacturing process development," European Journal of Operational Research, Elsevier, vol. 310(1), pages 238-248.

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