Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6734
Title: Folded overlapping variance estimators for simulation
Authors: Meterelliyoz Kuyzu, Melike
Alexopoulos, Christos
Goldsman, David
Keywords: Simulation output analysis
Area variance estimator
Overlapping variance estimator
Folded variance estimator
Issue Date: 2012
Publisher: Elsevier
Abstract: We propose and analyze a new class of estimators for the variance parameter of a steady-state simulation output process. The new estimators are computed by averaging individual estimators from "folded" standardized time series based on overlapping batches composed of consecutive observations. The folding transformation on each batch can be applied more than once to produce an entire set of estimators. We establish the limiting distributions of the proposed estimators as the sample size tends to infinity while the ratio of the sample size to the batch size remains constant. We give analytical and Monte Carlo results showing that, compared to their counterparts computed from nonoverlapping batches, the new estimators have roughly the same bias but smaller variance. In addition, these estimators can be computed with order-of-sample-size work. (C) 2012 Elsevier B.V. All rights reserved.
URI: https://doi.org/10.1016/j.ejor.2012.01.018
https://hdl.handle.net/20.500.11851/6734
ISSN: 0377-2217
1872-6860
Appears in Collections:İşletme Bölümü / Department of Management
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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