A pooled percentile estimator for parallel simulations. Issue 1 (2nd January 2022)

• Record Type: Journal Article
• Authors: Zhang, Qiong; Wang, Bo; Xie, Wei
• Is Part Of: Journal of simulation. Volume 16:Issue 1(2022)
• Page Start: 73
• Page End: 83
• Publication Date: 2022-01-02
• Subjects: Percentile estimation -- parallel computing -- stochastic simulation -- system risk measure; Operations research -- Periodicals; Mathematical models -- Periodicals; Simulation methods -- Periodicals; 511.805
• DOI: 10.1080/17477778.2020.1758597
• Languages: English
• ISSNs: 1747-7778

Abstract

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.