Note: Rule-Based Forecasting vs. Damped-Trend Exponential Smoothing
AbstractThis 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by INFORMS in its journal Management Science.
Volume (Year): 45 (1999)
Issue (Month): 8 (August)
combining forecasts; exponential smoothing; extrapolation; expert systems; judgment; rule-based forecasting;
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Gardner Jr., Everette S. & Diaz-Saiz, Joaquin, 2008. "Exponential smoothing in the telecommunications data," International Journal of Forecasting, Elsevier, vol. 24(1), pages 170-174.
- Taylor, James W., 2007. "Forecasting daily supermarket sales using exponentially weighted quantile regression," European Journal of Operational Research, Elsevier, vol. 178(1), pages 154-167, April.
- Bermudez, J.D. & Segura, J.V. & Vercher, E., 2006. "A decision support system methodology for forecasting of time series based on soft computing," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 177-191, November.
- Taylor, James W., 2003. "Exponential smoothing with a damped multiplicative trend," International Journal of Forecasting, Elsevier, vol. 19(4), pages 715-725.
- Adya, Monica & Collopy, Fred & Armstrong, J. Scott & Kennedy, Miles, 2001. "Automatic identification of time series features for rule-based forecasting," International Journal of Forecasting, Elsevier, vol. 17(2), pages 143-157.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc).
If references are entirely missing, you can add them using this form.