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

Author

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  • 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
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    Cited by:

    1. Armstrong, J. Scott & Brodie, Roderick J., 1999. "Forecasting for Marketing," MPRA Paper 81690, University Library of Munich, Germany.
    2. 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.
    3. 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.
    4. 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.
    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.

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    Keywords

    forecasting; marketing;

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