Note: Rule-Based Forecasting vs. Damped-Trend Exponential Smoothing
This paper evaluates the ex ante performance of rule-based time series forecasting systems proposed in earlier research. The author shows that comparable performance can be obtained with a simpler alternative, a damped-trend version of exponential smoothing fitted to minimize the Mean-Absolute-Deviation (MAD) criterion. The results suggest that the performance of rule-based systems would be improved through this alternative and that time series forecasters should consider MAD fits in model development.
Volume (Year): 45 (1999)
Issue (Month): 8 (August)
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- Fildes, Robert & Makridakis, Spyros, 1988. "Forecasting and loss functions," International Journal of Forecasting, Elsevier, vol. 4(4), pages 545-550.
- Fred Collopy & JS Armstrong, 2004.
"Rule-Based Forecasting: Development and Validation of an Expert Systems Approach to Combining Time Series Extrapolations,"
General Economics and Teaching
- Fred Collopy & J. Scott Armstrong, 1992. "Rule-Based Forecasting: Development and Validation of an Expert Systems Approach to Combining Time Series Extrapolations," Management Science, INFORMS, vol. 38(10), pages 1394-1414, October.
- Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
- Vokurka, Robert J. & Flores, Benito E. & Pearce, Stephen L., 1996. "Automatic feature identification and graphical support in rule-based forecasting: a comparison," International Journal of Forecasting, Elsevier, vol. 12(4), pages 495-512, December.
- Zellner, Arnold, 1986. "A tale of forecasting 1001 series : The Bayesian knight strikes again," International Journal of Forecasting, Elsevier, vol. 2(4), pages 491-494.
- Fildes, Robert, 1992. "The evaluation of extrapolative forecasting methods," International Journal of Forecasting, Elsevier, vol. 8(1), pages 81-98, June.
- Makridakis, Spyros & Hibon, Michele, 1991. "Exponential smoothing: The effect of initial values and loss functions on post-sample forecasting accuracy," International Journal of Forecasting, Elsevier, vol. 7(3), pages 317-330, November.
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