Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7408461 | International Journal of Forecasting | 2014 | 10 Pages |
Abstract
In this paper, transforms are used with exponential smoothing, in the quest for better forecasts. Two types of transforms are explored: those which are applied to a time series directly, and those which are applied indirectly to the prediction errors. The various transforms are tested on a large number of time series from the M3 competition, and ANOVA is applied to the results. We find that the non-transformed time series is significantly worse than some transforms on the monthly data, and on a distribution-based performance measure for both annual and quarterly data.
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Authors
Adrian N. Beaumont,