Tutorial on statistical analysis and experimental design in discrete event digital simulation experiments

Tutorial on statistical analysis and experimental design in discrete event digital simulation... TUTORIAL ON STATISTICAL ANALYSIS AND EXPERIMENTAL DESIGN IN DISCRETE EVENT DIGITAL SIMULATION EXPERIMENTS George S. Fishman Department of Administrative Sciences Yale University This tutorial reviews topics pertinent to the evaluation of results of discrete event digital simulation experiments and to the design of such experiments. The presentation includes: i. 2. alternative methods of estimating the variance of the sample mean of a process of interest computation of rough confidence intervals for the mean that acknowledge use of sample variance of sample mean in place of true variance of the sample mean bias due to initial conditions "rough" correlogram and spectrum estimation variance reduction as applied to experimental replication and the comparison of experimental results 3. 4. 5. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Tutorial on statistical analysis and experimental design in discrete event digital simulation experiments

Association for Computing Machinery — Jan 1, 1971

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Association for Computing Machinery
Copyright
Copyright © 1971 by ACM Inc.
D.O.I.
10.1145/800294.811465
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Abstract

TUTORIAL ON STATISTICAL ANALYSIS AND EXPERIMENTAL DESIGN IN DISCRETE EVENT DIGITAL SIMULATION EXPERIMENTS George S. Fishman Department of Administrative Sciences Yale University This tutorial reviews topics pertinent to the evaluation of results of discrete event digital simulation experiments and to the design of such experiments. The presentation includes: i. 2. alternative methods of estimating the variance of the sample mean of a process of interest computation of rough confidence intervals for the mean that acknowledge use of sample variance of sample mean in place of true variance of the sample mean bias due to initial conditions "rough" correlogram and spectrum estimation variance reduction as applied to experimental replication and the comparison of experimental results 3. 4. 5.

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