Exponential smoothing in the telecommunications data
نویسندگان
چکیده
Exponential smoothing methods gave poor forecast accuracy in Fildes et al.’s study of telecommunications time series. We reexamine this study and show that parameter optimization improves the accuracy of the Holt and damped trend methods. Further improvement occurs when the time series are trimmed to eliminate irrelevant early data, and when the methods are fitted to minimize the MAD rather than the MSE. Contrary to Fildes et al., we show that the damped trend is more accurate than Holt’s method. Because most of the telecommunications series display steady trends, we test the Theta method of forecasting and its derivative, simple exponential smoothing with drift. The Theta method proves disappointing, but simple exponential smoothing with drift is the best smoothing method for this data, giving about the same accuracy as the robust trend.
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تاریخ انتشار 2006