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Simulation: a statistical perspectiveDecember 1992
Publisher:
  • John Wiley & Sons, Inc.
  • 605 Third Ave. New York, NY
  • United States
ISBN:978-0-471-93055-6
Published:01 December 1992
Pages:
241
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Abstract

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Cited By

  1. van der Aalst W Process mining and simulation Proceedings of the 50th Computer Simulation Conference, (1-12)
  2. Rozinat A, Wynn M, van der Aalst W, ter Hofstede A and Fidge C (2009). Workflow simulation for operational decision support, Data & Knowledge Engineering, 68:9, (834-850), Online publication date: 1-Sep-2009.
  3. Rozinat A, Mans R, Song M and van der Aalst W (2009). Discovering simulation models, Information Systems, 34:3, (305-327), Online publication date: 1-May-2009.
  4. Kleijnen J Regression models and experimental designs Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come, (183-194)
  5. Kleijnen J White noise assumptions revisited Proceedings of the 38th conference on Winter simulation, (107-117)
  6. Kleijnen J, Sanchez S, Lucas T and Cioppa T (2005). State-of-the-Art Review, INFORMS Journal on Computing, 17:3, (263-289), Online publication date: 1-Jul-2005.
  7. ACM
    dos Santos M and Porta Nova A The main issues in nonlinear simulation metamodel estimation Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1, (502-509)
  8. Van Groenendaal W and Kleijnen J Identifying important factors in deterministic investment problems using design of experiments Proceedings of the 30th conference on Winter simulation, (713-718)
  9. Dussault J, Labrecque D, L‘Ecuyer P and Rubinstein R (2019). Combining the Stochastic Counterpart and Stochastic ApproximationMethods, Discrete Event Dynamic Systems, 7:1, (5-28), Online publication date: 1-Jan-1997.
  10. Kleijnen J Five-stage procedure for the evaluation of simulation models through statistical techniques Proceedings of the 28th conference on Winter simulation, (248-254)
  11. Kleijnen J, Bettonvil B and Van Groenendaal W Validation of trace-driven simulation models Proceedings of the 28th conference on Winter simulation, (352-359)
  12. van Groenendaal W and Kleijnen J Regression metamodels and design of experiments Proceedings of the 28th conference on Winter simulation, (1433-1439)
  13. Kleijnen J Sensitivity analysis and optimization in simulation Proceedings of the 27th conference on Winter simulation, (133-140)
  14. Pidd M An introduction to computer simulation Proceedings of the 26th conference on Winter simulation, (7-14)
  15. Donohue J Experimental designs for simulation Proceedings of the 26th conference on Winter simulation, (200-206)
  16. ACM
    Hassan S (1993). Port activity simulation, ACM SIGSIM Simulation Digest, 23:2, (17-36), Online publication date: 20-Dec-1993.
Contributors
  • Tilburg School of Economics and Management
  • Tilburg University

Reviews

Osman Balci

Twelve chapters compose this book: Introduction Random Numbers Sampling from Non-uniform Distributions Economic and Corporate Models Operations Research Models Simulation Software Statistical Applications Regression Metamodels Design of Experiments Tactical Aspects Verification and Validation Epilogue References are listed at the end of each chapter. Solutions to exercises, an author index, and a subject index are given at the end. Solutions to exercises that require computer programming are available on 3.5-inch disks for IBM and most IBM-compatible personal computers for a nominal fee. The purpose of the book is to provide basic knowledge of discrete event simulation and modeling. Chapters 4, 5, and 8 provide more than that. This work is an excellent textbook for an introductory simulation course designed to emphasize statistical aspects of discrete event simulation and modeling. It contains good exercises that will help students learn the material, especially with the software that can be purchased from the publisher. The book compares quite well to the other books in its class. It not only provides the basic simulation knowledge, but also ties simulation modeling to other types of modeling approaches. The book is a required source of knowledge for anyone dealing with statistical aspects of simulation.

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