Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Метод Тета× | ETS: Похибка, Тренд, Сезонне Експоненційне Згладжування× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 2000 | 2008 |
| Автор методу≠ | Assimakopoulos & Nikolopoulos | Hyndman, Koehler, Ord & Snyder (state space framework) |
| Тип≠ | Univariate time-series forecasting model | Exponential smoothing state space model |
| Основоположне джерело≠ | Assimakopoulos, V. & Nikolopoulos, K. (2000). The Theta Model: A Decomposition Approach to Forecasting. International Journal of Forecasting, 16(4), 521-530. DOI ↗ | Hyndman, R. J., Koehler, A. B., Ord, J. K. & Snyder, R. D. (2008). Forecasting with Exponential Smoothing: The State Space Approach. Springer. DOI ↗ |
| Інші назви≠ | theta model, theta forecasting, Theta Yöntemi — M3 Tahmin Yarışması Birincisi | exponential smoothing state space model, innovations state space model, Holt-Winters family, ETS — Hata/Trend/Mevsimsellik Üstel Düzleştirme |
| Пов'язані≠ | 4 | 5 |
| Підсумок≠ | The Theta Method is a univariate time-series forecasting model introduced by Assimakopoulos and Nikolopoulos in 2000. It decomposes a series into two theta lines that capture its long-run trend and its short-run dynamics, forecasts each line separately, and combines them by a weighted average. Its simplicity and accuracy made it the winner of the M3 forecasting competition. | 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. |
| ScholarGateНабір даних ↗ |
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