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On batch means in the simulation and statistics communities
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Source Winter Simulation Conference archive
Proceedings of the 27th conference on Winter simulation table of contents
Arlington, Virginia, United States
Pages: 297 - 302  
Year of Publication: 1995
ISBN:0-7803-3018-8
Author
Michael Sherman  Department of Statistics, Texas A&M University, College Station, TX
Sponsors
IIE : Institute of Industrial Engineers
SCS : Society for Computer Simulation
ASA : American Statistical Association
NIST : National Institue of Standards & Technology
IEEE-CS : Computer Society
IEEE-SMCS : Systems, Man & Cybernetics Society
ACM: Association for Computing Machinery
INFORMS/CS : Computer Science TC
SIGSIM: ACM Special Interest Group on Simulation and Modeling
Publisher
IEEE Computer Society  Washington, DC, USA
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ABSTRACT

Batching is a well known technique for estimating the variance of point estimators computed from simulation experiments. The batch statistic variance estimator is simply the (appropriately scaled) sample variance of the estimator computed on subsets of data. The simulation and statistics communities seem to be largely unaware of each other's results in this area. Some empirical and theoretical results from the simulation and statistics literature will be discussed and compared. In particular, we discuss the important issue of selecting batch size and present a new data based method for determining it. The basic idea is to empirically estimate the optimal batch size for a smaller simulation length, and then extrapolate using knowledge of the optimal order of magnitude of batch length for the original simulation length. We provide a small simulation showing the effectiveness of the proposed method.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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