Porovnat metody

	ETS: Error, Trend, Seasonal Exponential Smoothing	Holt-Wintersův trojitý exponenciální průměr
Obor	Ekonometrie	Ekonometrie
Rodina	Regression model	Regression model
Rok vzniku	2008	1960
Tvůrce	Hyndman, Koehler, Ord & Snyder (state space framework)	Charles C. Holt and Peter R. Winters
Typ	Exponential smoothing state space model	Exponential smoothing forecasting model
Původní zdroj	Hyndman, R. J., Koehler, A. B., Ord, J. K. & Snyder, R. D. (2008). Forecasting with Exponential Smoothing: The State Space Approach. Springer.	Winters, P. R. (1960). Forecasting Sales by Exponentially Weighted Moving Averages. Management Science, 6(3), 324-342.
Další názvy	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
Příbuzné	5	4
Shrnutí	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.