Comparer des méthodes

	Lissage exponentiel triple de Holt-Winters	Modèle structurel de séries temporelles (Modèle structurel de base)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1960	1990
Auteur d'origine	Charles C. Holt and Peter R. Winters	Andrew C. Harvey
Type	Exponential smoothing forecasting model	State-space (unobserved components) time series model
Source fondatrice	Winters, P. R. (1960). Forecasting Sales by Exponentially Weighted Moving Averages. Management Science, 6(3), 324-342.	Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. ISBN: 978-0521405737
Alias	triple exponential smoothing, Winters' method, Holt-Winters seasonal method, Holt-Winters Üçlü Üstel Düzleştirme	BSM, basic structural model, unobserved components model, Yapısal Zaman Serisi Modeli (BSM)
Apparentées	4	4
Résumé	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.	The Structural Time Series Model, in its Basic Structural Model (BSM) form, is Andrew Harvey's state-space approach that decomposes a series into separate stochastic trend, seasonal, cyclical, and irregular components. Developed in Harvey's 1990 treatment, it is prized for interpretability and component decomposition where ARIMA only delivers a black-box fit.