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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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
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 -