İşletme Bölümü / Department of Business Administration

Permanent URI for this collectionhttps://gcris3.etu.edu.tr/handle/20.500.11851/271

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Citation - Scopus: 6
Folded Overlapping Variance Estimators for Simulation
(Elsevier, 2012) Meterelliyoz Kuyzu, Melike; Alexopoulos, Christos; Goldsman, David
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.
Multiply Reflected Variance Estimators for Simulation
(IEEE, 2018) Dingeç, Kemal Dinçer; Alexopoulos, Christos; Goldsman, David; Meterelliyoz Kuyzu, Melike; Wilson, James R.
In 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.
Citation - Scopus: 4
Reflected variance estimators for simulation
(Taylor & Francis Inc, 2015) Meterelliyoz Kuyzu, Melike; Alexopoulos, Christos; Goldsman, David; Kalaycı, Tuba Aktaran
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.

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Browsing İşletme Bölümü / Department of Business Administration by Author "Alexopoulos, Christos"