Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Suavizado exponencial triple de Holt-Winters× | Modelo ARIMA (Autoregressive Integrated Moving Average)× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1960 | 2015 |
| Autor original≠ | Charles C. Holt and Peter R. Winters | Box & Jenkins (Box-Jenkins methodology) |
| Tipo≠ | Exponential smoothing forecasting model | Univariate time-series model |
| Fuente seminal≠ | Winters, 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 |
| Alias≠ | triple exponential smoothing, Winters' method, Holt-Winters seasonal method, Holt-Winters Üçlü Üstel Düzleştirme | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli |
| Relacionados≠ | 4 | 5 |
| Resumen≠ | 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. | 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). |
| ScholarGateConjunto de datos ↗ |
|
|