Сравнение методов

	Метод Тета	ETS: Экспоненциальное сглаживание с учетом ошибки, тренда и сезонности
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	2000	2008
Автор метода	Assimakopoulos & Nikolopoulos	Hyndman, Koehler, Ord & Snyder (state space framework)
Тип	Univariate time-series forecasting model	Exponential smoothing state space model
Основополагающий источник	Assimakopoulos, V. & Nikolopoulos, K. (2000). The Theta Model: A Decomposition Approach to Forecasting. International Journal of Forecasting, 16(4), 521-530.	Hyndman, R. J., Koehler, A. B., Ord, J. K. & Snyder, R. D. (2008). Forecasting with Exponential Smoothing: The State Space Approach. Springer.
Другие названия	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
Связанные	4	5
Сводка	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.