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    Rights statement: This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 296, 1, 2022 DOI: 10.1016/j.ejor.2021.05.052

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Fourier Trajectory Analysis For System Discrimination

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published

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Fourier Trajectory Analysis For System Discrimination. / Morgan, Lucy; Barton, Russell.
In: European Journal of Operational Research, Vol. 296, No. 1, 01.01.2022, p. 203-217.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Morgan, L & Barton, R 2022, 'Fourier Trajectory Analysis For System Discrimination', European Journal of Operational Research, vol. 296, no. 1, pp. 203-217.

APA

Morgan, L., & Barton, R. (2022). Fourier Trajectory Analysis For System Discrimination. European Journal of Operational Research, 296(1), 203-217.

Vancouver

Morgan L, Barton R. Fourier Trajectory Analysis For System Discrimination. European Journal of Operational Research. 2022 Jan 1;296(1):203-217. Epub 2021 Jun 5.

Author

Morgan, Lucy ; Barton, Russell. / Fourier Trajectory Analysis For System Discrimination. In: European Journal of Operational Research. 2022 ; Vol. 296, No. 1. pp. 203-217.

Bibtex

@article{589b9761ae514870ad467defd16583ad,
title = "Fourier Trajectory Analysis For System Discrimination",
abstract = "With few exceptions, simulation output analysis has focused on static characterizations, to determine a property of the steady-state distribution of a performance metric such as a mean, a quantile, or the distribution itself. Analyses often seek to overcome diffculties induced by autocorrelation of the output stream. But sample paths generated by stochastic simulation exhibit dynamic behavior that is characteristic of system structure and associated distributions. In this paper, we explore these dynamic characteristics, as capturedby the Fourier transform of a dynamic steady-state simulation trajectory. We find that Fourier coefficient magnitudes can have greater discriminatory power than the usual test statistics, and with simpler analysis resulting from the statistical independence of coefficient estimates at different frequencies.",
keywords = "Simulation, System discrimination, Fourier analysis",
author = "Lucy Morgan and Russell Barton",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 296, 1, 2022 DOI: 10.1016/j.ejor.2021.05.052",
year = "2022",
month = jan,
day = "1",
language = "English",
volume = "296",
pages = "203--217",
journal = "European Journal of Operational Research",
issn = "0377-2217",
publisher = "Elsevier Science B.V.",
number = "1",

}

RIS

TY - JOUR

T1 - Fourier Trajectory Analysis For System Discrimination

AU - Morgan, Lucy

AU - Barton, Russell

N1 - This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 296, 1, 2022 DOI: 10.1016/j.ejor.2021.05.052

PY - 2022/1/1

Y1 - 2022/1/1

N2 - With few exceptions, simulation output analysis has focused on static characterizations, to determine a property of the steady-state distribution of a performance metric such as a mean, a quantile, or the distribution itself. Analyses often seek to overcome diffculties induced by autocorrelation of the output stream. But sample paths generated by stochastic simulation exhibit dynamic behavior that is characteristic of system structure and associated distributions. In this paper, we explore these dynamic characteristics, as capturedby the Fourier transform of a dynamic steady-state simulation trajectory. We find that Fourier coefficient magnitudes can have greater discriminatory power than the usual test statistics, and with simpler analysis resulting from the statistical independence of coefficient estimates at different frequencies.

AB - With few exceptions, simulation output analysis has focused on static characterizations, to determine a property of the steady-state distribution of a performance metric such as a mean, a quantile, or the distribution itself. Analyses often seek to overcome diffculties induced by autocorrelation of the output stream. But sample paths generated by stochastic simulation exhibit dynamic behavior that is characteristic of system structure and associated distributions. In this paper, we explore these dynamic characteristics, as capturedby the Fourier transform of a dynamic steady-state simulation trajectory. We find that Fourier coefficient magnitudes can have greater discriminatory power than the usual test statistics, and with simpler analysis resulting from the statistical independence of coefficient estimates at different frequencies.

KW - Simulation

KW - System discrimination

KW - Fourier analysis

M3 - Journal article

VL - 296

SP - 203

EP - 217

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 1

ER -