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Computational Statistics

, Volume 16, Issue 1, pp 1–23 | Cite as

Sampling algorithms for estimating the mean of bounded random variables

  • Jian Cheng
Article

Summary

We show two distribution-independent algorithms to estimate the mean of bounded random variables, one with the knowledge of variance, the other without. These algorithms guarantee that the estimate is within the desired precision with an error probability less than or equal to the requirement. Some simplified stopping rules are also given.

Keywords

Algorithm Sampling Monte Carlo estimation Confidence intervals 

Notes

Acknowledgment

I would like to thank the anonymous reviewers and Marek J. Druzdzel for their useful comments that considerably improved the presentation of this paper.

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Copyright information

© Physica-Verlag 2001

Authors and Affiliations

  • Jian Cheng
    • 1
  1. 1.Decision Systems Laboratory, School of Information SciencesUniversity of PittsburghPittsburghUSA

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