方法对比
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| ETS：误差、趋势、季节性指数平滑× | 霍尔特-温特斯三指数平滑法× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2008 | 1960 |
| 提出者≠ | Hyndman, Koehler, Ord & Snyder (state space framework) | Charles C. Holt and Peter R. Winters |
| 类型≠ | Exponential smoothing state space model | Exponential smoothing forecasting model |
| 开创性文献≠ | 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 ↗ |
| 别名 | 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 |
| 相关≠ | 5 | 4 |
| 摘要≠ | 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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