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| ETS: Wykładnicze wygładzanie z uwzględnieniem błędu, trendu i sezonowości× | Potrójne wygładzanie wykładnicze Holta-Wintersa× | |
|---|---|---|
| Dziedzina | Ekonometria | Ekonometria |
| Rodzina | Regression model | Regression model |
| Rok powstania≠ | 2008 | 1960 |
| Twórca≠ | Hyndman, Koehler, Ord & Snyder (state space framework) | Charles C. Holt and Peter R. Winters |
| Typ≠ | Exponential smoothing state space model | Exponential smoothing forecasting model |
| Źródło pierwotne≠ | Hyndman, R. J., Koehler, A. B., Ord, J. K. & Snyder, R. D. (2008). Forecasting with Exponential Smoothing: The State Space Approach. Springer. DOI ↗ | Winters, P. R. (1960). Forecasting Sales by Exponentially Weighted Moving Averages. Management Science, 6(3), 324-342. DOI ↗ |
| Inne nazwy | exponential smoothing state space model, innovations state space model, Holt-Winters family, ETS — Hata/Trend/Mevsimsellik Üstel Düzleştirme | triple exponential smoothing, Winters' method, Holt-Winters seasonal method, Holt-Winters Üçlü Üstel Düzleştirme |
| Pokrewne≠ | 5 | 4 |
| Podsumowanie≠ | ETS is a comprehensive exponential smoothing framework that automatically selects additive or multiplicative combinations of the error (E), trend (T) and seasonal (S) components of a time series. Formalised as an innovations state space model by Hyndman, Koehler, Ord and Snyder in 2008, it unifies and generalises the Holt-Winters family of forecasting methods. | Holt-Winters triple exponential smoothing is a forecasting model that extends Holt's double smoothing by adding a seasonal component, introduced by Peter Winters in 1960 building on Charles Holt's work. It tracks three evolving quantities — level, trend, and season — and combines them to forecast a continuous time series. |
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