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dc.contributor.authorDingeç, Kemal Dinçer
dc.contributor.authorAlexopoulos, Christos
dc.contributor.authorGoldsman, David
dc.contributor.authorMeterelliyoz, Melike
dc.contributor.authorWilson, James R.
dc.date.accessioned2020-01-27T06:41:29Z
dc.date.available2020-01-27T06:41:29Z
dc.date.issued2018
dc.identifier.citationDingeç, K. D., Alexopoulos, C., Goldsman, D., Meterelliyoz, M., & Wilson, J. R. (2018, December). Multiply reflected variance estimators for simulation. In 2018 Winter Simulation Conference (WSC) (pp. 1670-1681). IEEE.en_US
dc.identifier.issn0891-7736
dc.identifier.urihttps://ieeexplore.ieee.org/abstract/document/8632554
dc.identifier.uri10.1109/WSC.2018.8632554
dc.identifier.urihttp://hdl.handle.net/20.500.11851/3265
dc.description.abstractIn a previous article, we studied a then-new class of standardized time series (STS) estimators for the asymptotic variance parameter of a stationary simulation output process. Those estimators invoke the well-known reflection principle of Brownian motion on the suitably standardized original output process to compute several "reflected" realizations of the STS, each of which is based on a single reflection point. We then calculated variance-and mean-squared-error-optimal linear combinations of the estimators formed from the singly reflected realizations. The current paper repeats the exercise except that we now examine the efficacy of employing multiple reflection points on each reflected realization of the STS. This scheme provides additional flexibility that can be exploited to produce estimators that are superior to their single-reflection-point predecessors with respect to mean-squared error. We illustrate the enhanced performance of the multiply reflected estimators via exact calculations and Monte Carlo experiments.en_US
dc.description.sponsorshipNational Science FoundationNational Science Foundation (NSF) [CMMI-1232998/1233141]
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectComputer Science, Theory & Methodsen_US
dc.titleMultiply reflected variance estimators for simulationen_US
dc.typeconferenceObjecten_US
dc.relation.journal2018 WINTER SIMULATION CONFERENCE (WSC)en_US
dc.contributor.departmentTOBB ETU, Faculty of Economics and Administrative Sciences, Department of Managementen_US
dc.contributor.departmentTOBB ETÜ, İktisadi ve İdari Bilimler Fakültesi, İşletme Bölümütr_TR
dc.identifier.startpage1670
dc.identifier.endpage1681
dc.identifier.scopus2-s2.0-85062628576
dc.contributor.tobbetuauthorMeterelliyoz, Melike
dc.contributor.YOKid36211
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıtr_TR


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