Using nonparametric statistics in simulation analysis: a review
Pages 141 - 146
Abstract
Techniques that make the minimum of assumptions about the underlying characteristics of the simulation output series are particularly useful for simulation analysis. This tutorial discusses robust non-parametric techniques with immediate applicability to such crucial steps in simulation analysis as sampling, experimental design, and output analysis. Algorithms are provided for various tasks.
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Index Terms
- Using nonparametric statistics in simulation analysis: a review
Comments
Information & Contributors
Information
Published In
December 1995
1493 pages
ISBN:0780330188
- Chairmen:
- William R. Lilegdon,
- David Goldsman,
- Editors:
- Christos Alexopoulos,
- Keebom Kang
Sponsors
- IIE: Institute of Industrial Engineers
- IEEE-SMCS: Systems, Man & Cybernetics Society
- INFORMS/CS: Computer Science TC
- ASA: American Statistical Association
- ACM: Association for Computing Machinery
- SCS: Society for Computer Simulation
- SIGSIM: ACM Special Interest Group on Simulation and Modeling
- IEEE-CS: Computer Society
- NIST: National Institute of Standards & Technology
Publisher
IEEE Computer Society
United States
Publication History
Published: 01 December 1995
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