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Run length not required: Optimal-mse dynamic batch means estimators for steady-state simulations

Wheyming Tina Song and Mingchang Chih

European Journal of Operational Research, 2013, vol. 229, issue 1, 114-123

Abstract: This paper addresses the estimation of the variance of the sample mean from steady-state simulations without requiring the knowledge of simulation run length a priori. Dynamic batch means is a new and useful approach to implementing the traditional batch means in limited memory without the knowledge of the simulation run length. However, existing dynamic batch means estimators do not allow one to control the value of batch size, which is the performance parameter of the batch means estimators. In this work, an algorithm is proposed based on two dynamic batch means estimators to dynamically estimate the optimal batch size as the simulation runs. The simulation results show that the proposed algorithm requires reasonable computation time and possesses good statistical properties such as small mean-squared-error (mse).

Keywords: Variance of the sample mean; Simulation; Batch means estimator; Optimal batch size; Mean-squared-error (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:229:y:2013:i:1:p:114-123

DOI: 10.1016/j.ejor.2012.10.019

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European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

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