IDEAS home Printed from https://ideas.repec.org/a/wly/navlog/v25y1978i4p715-725.html
   My bibliography  Save this article

Refined prediction for linear regression models

Author

Listed:
  • J. L. Hess
  • R. F. Gunst

Abstract

Adequate prediction of a response variable using a multiple linear regression model is shown in this article to be related to the presence of multicollinearities among the predictor variables. If strong multicollinearities are present in the data, this information can be used to determine when prediction is likely to be accurate. A region of prediction, R, is proposed as a guide for prediction purposes. This region is related to a prediction interval when the matrix of predictor variables is of full column rank, but it can also be used when the sample is undersized. The Gorman‐Toman ten‐variable data is used to illustrate the effectiveness of the region R.

Suggested Citation

  • J. L. Hess & R. F. Gunst, 1978. "Refined prediction for linear regression models," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 25(4), pages 715-725, December.
    • Handle: RePEc:wly:navlog:v:25:y:1978:i:4:p:715-725
    DOI: 10.1002/nav.3800250413
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/nav.3800250413
    Download Restriction: no
    File URL: https://libkey.io/10.1002/nav.3800250413?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
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:wly:navlog:v:25:y:1978:i:4:p:715-725. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1931-9193 .

    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.