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ETS: Erro, Tendência, Suavização Exponencial Sazonal×Holt-Winters×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem20081960
Autor originalHyndman, Koehler, Ord & Snyder (state space framework)Charles C. Holt and Peter R. Winters
TipoExponential smoothing state space modelExponential smoothing forecasting model
Fonte seminalHyndman, R. J., Koehler, A. B., Ord, J. K. & Snyder, R. D. (2008). Forecasting with Exponential Smoothing: The State Space Approach. Springer. DOI ↗Winters, P. R. (1960). Forecasting Sales by Exponentially Weighted Moving Averages. Management Science, 6(3), 324-342. DOI ↗
Outros nomesexponential smoothing state space model, innovations state space model, Holt-Winters family, ETS — Hata/Trend/Mevsimsellik Üstel Düzleştirmetriple exponential smoothing, Winters' method, Holt-Winters seasonal method, Holt-Winters Üçlü Üstel Düzleştirme
Relacionados54
ResumoETS 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.
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ScholarGateComparar métodos: ETS Model · Holt-Winters. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare