Implementable MSE-optimal dynamic partial-overlapping batch means estimators for steady-state simulations

Estimating the variance of the sample mean from a stochastic process is essential in assessing the quality of using the sample mean to estimate the population mean which is the fundamental question in simulation experiments. Most existing studies for estimating the variance of the sample mean from s...

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Bibliographic Details
Published in2008 Winter Simulation Conference pp. 426 - 435
Main Authors Song, Wheyming Tina, Mingchang Chih
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2008
Subjects
Analytical models
Communication networks
Computational modeling
Context modeling
Cranes
Delay effects
Industrial engineering
Mean-Squared-Error
Probability
Simulation
Steady-state
Stochastic processes
Variance of the Sample Mean
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Summary:Estimating the variance of the sample mean from a stochastic process is essential in assessing the quality of using the sample mean to estimate the population mean which is the fundamental question in simulation experiments. Most existing studies for estimating the variance of the sample mean from simulation output assume simulation run length is known in advance. This paper proposes an implementable batch-size selection procedure for estimating the variance of the sample mean without requiring that the sample size or simulation run length a priori.
ISBN:9781424427079
142442707X
ISSN:0891-7736
1558-4305
DOI:10.1109/WSC.2008.4736097