IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v16y1986i6p100-107.html
   My bibliography  Save this article

An Evaluation of Rules for Selecting an Extrapolation Model on Yearly Sales Forecasts

Author

Listed:
  • Steven P. Schnaars

    (Baruch College, The City University of New York, 17 Lexington Avenue, New York, New York 10010)

Abstract

Six rules are used to select among seven exponential smoothing models (to pick the model that yields the lowest error on a fit to historical data). Comparisons of accuracy are made among forecasts generated by the selection rules and the individual smoothing models. The results indicate that the use of rules leads to increases in accuracy. A combination of selection rules led to the most accurate forecasts. The rules also led to lower variances in the accuracy of forecasts, that is, they help to avoid large errors.

Suggested Citation

  • Steven P. Schnaars, 1986. "An Evaluation of Rules for Selecting an Extrapolation Model on Yearly Sales Forecasts," Interfaces, INFORMS, vol. 16(6), pages 100-107, December.
    • Handle: RePEc:inm:orinte:v:16:y:1986:i:6:p:100-107
    DOI: 10.1287/inte.16.6.100
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.16.6.100
    Download Restriction: no
    File URL: https://libkey.io/10.1287/inte.16.6.100?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. de Menezes, Lilian M. & W. Bunn, Derek & Taylor, James W., 2000. "Review of guidelines for the use of combined forecasts," European Journal of Operational Research, Elsevier, vol. 120(1), pages 190-204, January.
    2. Thomson, Mary E. & Pollock, Andrew C. & Önkal, Dilek & Gönül, M. Sinan, 2019. "Combining forecasts: Performance and coherence," International Journal of Forecasting, Elsevier, vol. 35(2), pages 474-484.
    3. Armstrong, J. Scott & Brodie, Roderick J., 1999. "Forecasting for Marketing," MPRA Paper 81690, University Library of Munich, Germany.
    4. J. S. Armstrong & R. Brodie & S. McIntyre, 2005. "Forecasting Methods for Marketing:* Review of Empirical Research," General Economics and Teaching 0502023, University Library of Munich, Germany.
    5. Tashman, Leonard J. & Kruk, Joshua M., 1996. "The use of protocols to select exponential smoothing procedures: A reconsideration of forecasting competitions," International Journal of Forecasting, Elsevier, vol. 12(2), pages 235-253, June.

    More about this item

    Keywords

    forecasting; marketing;

    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:inm:orinte:v:16:y:1986:i:6:p:100-107. 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.