IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v39y1991i4p583-591.html
   My bibliography  Save this article

Using Common Random Numbers and Control Variates in Multiple-Comparison Procedures

Author

Listed:
  • Wei-Ning Yang

    (Ohio State University, Columbus, Ohio)

  • Barry L. Nelson

    (Ohio State University, Columbus, Ohio)

Abstract

This paper considers the determination of the relative merits of two or more system designs via stochastic simulation experiments by constructing simultaneous interval estimates of certain differences in expected performance. Tukey's all-pairwise-comparisons procedure, Hsu's multiple-comparisons-with-the-best procedure, and Dunnett's multiple-comparisons-with-a-control procedure are standard methods for making such comparisons. We propose refinements for all three procedures through the use of two variance reduction techniques: common random numbers and control variates. We show that the proposed procedures are better than the standard multiple-comparison procedures in the sense that they have a larger probability of containing the true difference and, at the same time, not containing zero when a difference exists.

Suggested Citation

  • Wei-Ning Yang & Barry L. Nelson, 1991. "Using Common Random Numbers and Control Variates in Multiple-Comparison Procedures," Operations Research, INFORMS, vol. 39(4), pages 583-591, August.
    • Handle: RePEc:inm:oropre:v:39:y:1991:i:4:p:583-591
    DOI: 10.1287/opre.39.4.583
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.39.4.583
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.39.4.583?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. L. Dai & C. H. Chen, 1997. "Rates of Convergence of Ordinal Comparison for Dependent Discrete Event Dynamic Systems," Journal of Optimization Theory and Applications, Springer, vol. 94(1), pages 29-54, July.
    2. Barry L. Nelson & David Goldsman, 2001. "Comparisons with a Standard in Simulation Experiments," Management Science, INFORMS, vol. 47(3), pages 449-463, March.
    3. Diana M. Negoescu & Peter I. Frazier & Warren B. Powell, 2011. "The Knowledge-Gradient Algorithm for Sequencing Experiments in Drug Discovery," INFORMS Journal on Computing, INFORMS, vol. 23(3), pages 346-363, August.
    4. Jing Xie & Peter I. Frazier & Stephen E. Chick, 2016. "Bayesian Optimization via Simulation with Pairwise Sampling and Correlated Prior Beliefs," Operations Research, INFORMS, vol. 64(2), pages 542-559, April.
    5. Michael C. Fu & Jian-Qiang Hu & Chun-Hung Chen & Xiaoping Xiong, 2007. "Simulation Allocation for Determining the Best Design in the Presence of Correlated Sampling," INFORMS Journal on Computing, INFORMS, vol. 19(1), pages 101-111, February.
    6. Huashuai Qu & Ilya O. Ryzhov & Michael C. Fu & Zi Ding, 2015. "Sequential Selection with Unknown Correlation Structures," Operations Research, INFORMS, vol. 63(4), pages 931-948, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:oropre:v:39:y:1991:i:4:p:583-591. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.