IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v41y1995i7p1202-1223.html
   My bibliography  Save this article

Simulation-Based Estimation of Proportions

Author

Listed:
  • Kimmo E. E. Raatikainen

    (University of Helsinki, Department of Computer Science, P.O. Box 26 (Teollisuuskatu 23), FIN-00014 University of Helsinki, Finland)

Abstract

Simulated estimates for several proportions are needed in many simulation studies. We propose a method for controlling the length of a simulation run so that the proportions estimated satisfy a prespecified precision requirement. The method applies the arcsin transform in order to generate confidence intervals with the desired width. The Bonferroni inequality is applied in a new way to construct a rectangular confidence area for the proportions being estimated. Since we are using the Bonferroni inequality, we can use the existing methods developed for estimating the variance of a single mean. The properties of the method proposed depend on three factors: 1) the arcsin transform, 2) the proposed way of applying the Bonferroni inequality, and 3) the method for estimating the variance. We examine the effects that the transform and the way of applying the Bonferroni inequality have. Empirical results indicate that the method provides estimates that satisfy the prespecified precision requirement, when the spectral method is used to estimate the variances of the proportions. In addition, simulation runs, when estimating either several proportions or the corresponding mean, are about the same lengths.

Suggested Citation

  • Kimmo E. E. Raatikainen, 1995. "Simulation-Based Estimation of Proportions," Management Science, INFORMS, vol. 41(7), pages 1202-1223, July.
    • Handle: RePEc:inm:ormnsc:v:41:y:1995:i:7:p:1202-1223
    DOI: 10.1287/mnsc.41.7.1202
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.41.7.1202
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.41.7.1202?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. Nikolic, Nebojsa, 2008. "Statistical integration of Erlang's equations," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1487-1493, June.

    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:ormnsc:v:41:y:1995:i:7:p:1202-1223. 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.