Note: Rule-Based Forecasting vs. Damped-Trend Exponential Smoothing
Published Online:1 Aug 1999https://doi.org/10.1287/mnsc.45.8.1169
References
- Error measures for generalizing about forecasting methods: Empirical comparisons. Internat. J. Forecasting (1992) 8:69–80Crossref, Google Scholar
- Rule-based forecasting: Development and validation of an expert systems approach to combining time series extrapolations. Management Sci. (1992) 38:1394–1414Link, Google Scholar
- The evaluation of extrapolative forecasting methods. Internat. J. Forecasting (1992) 8:81–98Crossref, Google Scholar
- Forecasting and loss functions. Internat. J. Forecasting (1988) 4:545–550Crossref, Google Scholar
- Exponential smoothing: The state of the art. J. Forecasting (1985) 4:1–28Crossref, Google Scholar
- Forecasting trends in time series. Management Sci. (1985) 31:1237–1246Link, Google Scholar
- The accuracy of extrapolation (time series) methods: Results of a forecasting competition. J. Forecasting (1982) 1:111–153Crossref, Google Scholar
- Exponential smoothing: The effect of initial values and loss functions on post-sample forecasting accuracy. Internat. J. Forecasting (1991) 7:317–330Crossref, Google Scholar
- Delphus, Inc.Peer Planner (1997) (Morristown, NJ)Google Scholar
- Automatic feature identification and graphical support in rule-based forecasting: A comparison. Internat. J. Forecasting (1996) 12:495–512Crossref, Google Scholar
- Estimating time series models using the relevant forecast evaluation criterion. J. Roy. Statist. Soc. Ser. A (1984) 147(Part 3):484–487Crossref, Google Scholar
- A tale of forecasting 1001 series: The Bayesian Knight strikes again. Internat. J. Forecasting (1986) 2:491–494Crossref, Google Scholar

