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Batch Size Effects in the Analysis of Simulation Output

Citations

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Cited by:

  1. Enver Yücesan, 1993. "Randomization tests for initialization bias in simulation output," Naval Research Logistics (NRL), John Wiley & Sons, vol. 40(5), pages 643-663, August.
  2. Song, Wheyming Tina & Chih, Mingchang, 2013. "Run length not required: Optimal-mse dynamic batch means estimators for steady-state simulations," European Journal of Operational Research, Elsevier, vol. 229(1), pages 114-123.
  3. Song, Wheyming Tina, 1996. "On the estimation of optimal batch sizes in the analysis of simulation output," European Journal of Operational Research, Elsevier, vol. 88(2), pages 304-319, January.
  4. Srinagesh Gavirneni & Douglas J. Morrice & Peter Mullarkey, 2004. "Simulation Helps Maxager Shorten Its Sales Cycle," Interfaces, INFORMS, vol. 34(2), pages 87-96, April.
  5. Kenneth W. Bauer & James R. Wilson, 1992. "Control‐variate selection criteria," Naval Research Logistics (NRL), John Wiley & Sons, vol. 39(3), pages 307-321, April.
  6. Barry L. Nelson, 2004. "50th Anniversary Article: Stochastic Simulation Research in Management Science," Management Science, INFORMS, vol. 50(7), pages 855-868, July.
  7. Christos Alexopoulos & David Goldsman & Gamze Tokol, 2001. "Properties of Batched Quadratic-Form Variance Parameter Estimators for Simulations," INFORMS Journal on Computing, INFORMS, vol. 13(2), pages 149-156, May.
  8. Ilya O. Ryzhov & Warren B. Powell, 2011. "Information Collection on a Graph," Operations Research, INFORMS, vol. 59(1), pages 188-201, February.
  9. Driessen, M.A. & van Houtum, G.J. & Zijm, W.H.M. & Rustenburg, W.D., 2020. "Capacity assignment in repair shops with high material uncertainty," International Journal of Production Economics, Elsevier, vol. 221(C).
  10. Song, Wheyming Tina, 2019. "The Song rule outperforms optimal-batch-size variance estimators in simulation output analysis," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1072-1082.
  11. Munoz, F.D. & Hobbs, B.F. & Watson, J.-P., 2016. "New bounding and decomposition approaches for MILP investment problems: Multi-area transmission and generation planning under policy constraints," European Journal of Operational Research, Elsevier, vol. 248(3), pages 888-898.
  12. Muñoz Negrón, David F. & Muñoz Medina, Diego F., 2009. "Bayesian Forecastings For Automobile Parts Using Stochastic Simulation," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 14(27), pages 7-20.
  13. Jack P. C. Kleijnen & Russell C. H. Cheng & Bert Bettonvil, 2001. "Validation of Trace-Driven Simulation Models: Bootstrap Tests," Management Science, INFORMS, vol. 47(11), pages 1533-1538, November.
  14. Mingchang Chih, 2019. "An Insight into the Data Structure of the Dynamic Batch Means Algorithm with Binary Tree Code," Mathematics, MDPI, vol. 7(9), pages 1-8, August.
  15. Tûba Aktaran‐Kalaycı & Christos Alexopoulos & Nilay Tanık Argon & David Goldsman & James R. Wilson, 2007. "Exact expected values of variance estimators for simulation," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(4), pages 397-410, June.
  16. Morgan, Lucy E. & Barton, Russell R., 2022. "Fourier trajectory analysis for system discrimination," European Journal of Operational Research, Elsevier, vol. 296(1), pages 203-217.
  17. Jack P. C. Kleijnen & Susan M. Sanchez & Thomas W. Lucas & Thomas M. Cioppa, 2005. "State-of-the-Art Review: A User’s Guide to the Brave New World of Designing Simulation Experiments," INFORMS Journal on Computing, INFORMS, vol. 17(3), pages 263-289, August.
  18. Chaitra H. Nagaraja & Haikady N. Nagaraja, 2020. "Distribution‐free Approximate Methods for Constructing Confidence Intervals for Quantiles," International Statistical Review, International Statistical Institute, vol. 88(1), pages 75-100, April.
  19. Christos Alexopoulos & Nilay Tanık Argon & David Goldsman & Natalie M. Steiger & Gamze Tokol & James R. Wilson, 2007. "Efficient Computation of Overlapping Variance Estimators for Simulation," INFORMS Journal on Computing, INFORMS, vol. 19(3), pages 314-327, August.
  20. Song, Wheyming T. & Chih, Mingchang, 2010. "Extended dynamic partial-overlapping batch means estimators for steady-state simulations," European Journal of Operational Research, Elsevier, vol. 203(3), pages 640-651, June.
  21. Christos Alexopoulos & Nilay Tanık Argon & David Goldsman & Gamze Tokol & James R. Wilson, 2007. "Overlapping Variance Estimators for Simulation," Operations Research, INFORMS, vol. 55(6), pages 1090-1103, December.
  22. David F. Muñoz & Peter W. Glynn, 2001. "Multivariate Standardized Time Series for Steady-State Simulation Output Analysis," Operations Research, INFORMS, vol. 49(3), pages 413-422, June.
  23. Karen T. Hicklin & Julie S. Ivy & James R. Wilson & Fay Cobb Payton & Meera Viswanathan & Evan R. Myers, 2019. "Simulation model of the relationship between cesarean section rates and labor duration," Health Care Management Science, Springer, vol. 22(4), pages 635-657, December.
  24. Kannan, V. R. & Ghosh, S., 1995. "Using dynamic cellular manufacturing to simplify scheduling in cell based production systems," Omega, Elsevier, vol. 23(4), pages 443-452, August.
  25. Kin Wai Chan & Chun Yip Yau, 2017. "High-order Corrected Estimator of Asymptotic Variance with Optimal Bandwidth," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(4), pages 866-898, December.
  26. David Goldsman & Keebom Kang & Seong‐Hee Kim & Andrew F. Seila & Gamze Tokol, 2007. "Combining standardized time series area and Cramér–von Mises variance estimators," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(4), pages 384-396, June.
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