IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v39y1991i3p519-523.html
   My bibliography  Save this article

How Many Forecasters Do You Really Have? Mahalanobis Provides the Intuition for the Surprising Clemen and Winkler Result

Author

Listed:
  • Donald G. Morrison

    (University of California, Los Angeles, California)

  • David C. Schmittlein

    (University of Pennsylvania, Philadelphia, Pennsylvania)

Abstract

How to combine expert opinions is an issue that has many aspects and even more “answers.” The problem addressed here is the incremental information an additional expert brings when he or she is correlated with the existing experts. R. T. Clemen and R. L. Winkler derive an algebraic formula that gives the surprising answer—usually very little. In this paper, we provide the geometrical intuition behind the Clemen and Winkler result. We also show how the Clemen and Winkler formula breaks down (i.e., gives bizarre results) as the error covariance structure approaches singularity.

Suggested Citation

  • Donald G. Morrison & David C. Schmittlein, 1991. "How Many Forecasters Do You Really Have? Mahalanobis Provides the Intuition for the Surprising Clemen and Winkler Result," Operations Research, INFORMS, vol. 39(3), pages 519-523, June.
    • Handle: RePEc:inm:oropre:v:39:y:1991:i:3:p:519-523
    DOI: 10.1287/opre.39.3.519
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.39.3.519
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.39.3.519?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. Jones, Christopher S. & Finn, John M. & Hengartner, Nicolas, 2008. "Regression with strongly correlated data," Journal of Multivariate Analysis, Elsevier, vol. 99(9), pages 2136-2153, October.
    2. Jagmohan S. Raju & Abhik Roy, 2000. "Market Information and Firm Performance," Management Science, INFORMS, vol. 46(8), pages 1075-1084, August.
    3. Mukhopadhyay, Samar K. & Yue, Xiaohang & Zhu, Xiaowei, 2011. "A Stackelberg model of pricing of complementary goods under information asymmetry," International Journal of Production Economics, Elsevier, vol. 134(2), pages 424-433, December.
    4. Yan, Ruiliang & Ghose, Sanjoy, 2010. "Forecast information and traditional retailer performance in a dual-channel competitive market," Journal of Business Research, Elsevier, vol. 63(1), pages 77-83, January.
    5. Zhiqiang Zheng & Balaji Padmanabhan, 2007. "Constructing Ensembles from Data Envelopment Analysis," INFORMS Journal on Computing, INFORMS, vol. 19(4), pages 486-496, November.

    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:3:p:519-523. 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.