On the estimation of optimal batch sizes in the analysis of simulation output

DOI10.1016/0377-2217(94)00204-5zbMath0913.90109OpenAlexW2090475279MaRDI QIDQ1266594

Wheyming Tina Song

Publication date: 7 October 1998

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0377-2217(94)00204-5

zbMATH Keywords

autoregressive processesstochastic simulationvariance of point estimators\(M/M/1\) queueingoptimal batch sizesymmetric two-state Markov chain models

Mathematics Subject Classification ID

Queues and service in operations research (90B22)

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Local linear quantile estimation for nonstationary time series ⋮ New recursive estimators of the time-average variance constant ⋮ The Song rule outperforms optimal-batch-size variance estimators in simulation output analysis ⋮ On the robustness of batching estimators. ⋮ Simulation output analysis using the threshold bootstrap ⋮ Extended dynamic partial-overlapping batch means estimators for steady-state simulations ⋮ Convergence rate of plugin estimates for functional parameters with applications to locally-stationary time-series ⋮ A three-class variance swapping technique for simulation experiments ⋮ Run length not required: optimal-MSE dynamic batch means estimators for steady-state simulations

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