Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/1606
Title: Reflected variance estimators for simulation
Authors: Meterelliyoz Kuyzu, Melike
Alexopoulos, Christos
Goldsman, David
Kalaycı, Tuba Aktaran
36211
Keywords: Cramr-von Mises variance estimator
area variance estimator
Stationary simulation output analysis
reflected variance estimator
Issue Date: 2015
Publisher: Taylor & Francis Inc
Source: Meterelliyoz, M., Alexopoulos, C., Goldsman, D., & Aktaran-Kalayci, T. (2015). Reflected variance estimators for simulation. IIE Transactions, 47(11), 1185-1202.
Abstract: We propose a new class of estimators for the asymptotic variance parameter of a stationary simulation output process. The estimators are based on Standardized Time Series (STS) functionals that converge to Brownian bridges that are themselves derived from appropriately reflected Brownian motions. The main result is that certain linear combinations of reflected estimators have substantially smaller variances than their constituents. We illustrate the performance of the new estimators via Monte Carlo experiments. These experiments show that the reflected estimators behave as expected and, in addition, perform better than certain competitors such as nonoverlapping batch means estimators and STS folded estimators.
URI: https://ieeexplore.ieee.org/document/5679063
https://hdl.handle.net/20.500.11851/1606
ISSN: 0740-817X
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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