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Τριπλή Εκθετική Εξομάλυνση Holt-Winters×Μοντέλο ARIMA (Autoregressive Integrated Moving Average)×
ΠεδίοΟικονομετρίαΟικονομετρία
ΟικογένειαRegression modelRegression model
Έτος προέλευσης19602015
ΔημιουργόςCharles C. Holt and Peter R. WintersBox & Jenkins (Box-Jenkins methodology)
ΤύποςExponential smoothing forecasting modelUnivariate time-series model
Θεμελιώδης πηγήWinters, P. R. (1960). Forecasting Sales by Exponentially Weighted Moving Averages. Management Science, 6(3), 324-342. DOI ↗Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021
Εναλλακτικές ονομασίεςtriple exponential smoothing, Winters' method, Holt-Winters seasonal method, Holt-Winters Üçlü Üstel DüzleştirmeBox-Jenkins model, ARIMA(p,d,q), ARIMA Modeli
Συναφείς45
ΣύνοψηHolt-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.ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).
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ScholarGateΣύγκριση μεθόδων: Holt-Winters · ARIMA. Ανακτήθηκε στις 2026-06-18 από https://scholargate.app/el/compare