Сравнение методов

	Простое и двойное экспоненциальное сглаживание (SES / Холт)	Тройное экспоненциальное сглаживание Хольта-Винтерса
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	1957	1960
Автор метода	Robert G. Brown (SES); Charles C. Holt (linear trend)	Charles C. Holt and Peter R. Winters
Тип	Exponential smoothing forecasting model	Exponential smoothing forecasting model
Основополагающий источник	Brown, R. G. (1959). Statistical Forecasting for Inventory Control. McGraw-Hill.	Winters, P. R. (1960). Forecasting Sales by Exponentially Weighted Moving Averages. Management Science, 6(3), 324-342.
Другие названия	SES, Holt's linear trend method, exponential smoothing forecasting, Basit ve Çift Üstel Düzleştirme (SES / Holt)	triple exponential smoothing, Winters' method, Holt-Winters seasonal method, Holt-Winters Üçlü Üstel Düzleştirme
Связанные	3	4
Сводка	Exponential smoothing is a family of basic time-series forecasting models in which each new observation updates a smoothed estimate by a weighting parameter. Simple exponential smoothing (SES), introduced by Robert G. Brown in 1959, forecasts series with a stable level, while Holt's double exponential smoothing, introduced by Charles C. Holt in 1957, adds a trend term using the parameters alpha and beta.	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.