Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| SARIMA (Seasonal ARIMA)× | SARIMAX× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine | 2015 | 2015 |
| Auteur d'origine≠ | Box & Jenkins (seasonal extension of ARIMA) | Box & Jenkins (ARIMA framework); SARIMAX extension with exogenous regressors |
| Type≠ | Seasonal time-series model | Seasonal time-series regression model |
| Source fondatrice≠ | 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 | Hyndman, R. J. & Athanasopoulos, G. (2021). Forecasting: Principles and Practice (3rd ed.). OTexts. link ↗ |
| Alias≠ | seasonal ARIMA, Box-Jenkins seasonal model, SARIMA — Mevsimsel ARIMA | seasonal ARIMA with exogenous variables, SARIMA with regressors, ARIMAX, SARIMAX — Dışsal Değişkenli Mevsimsel ARIMA |
| Apparentées≠ | 5 | 4 |
| Résumé≠ | SARIMA is a seasonal extension of the Box-Jenkins ARIMA model that adds seasonal differencing and seasonal autoregressive and moving-average terms. Developed within the Box, Jenkins, Reinsel and Ljung framework (5th edition, 2015), it forecasts series whose pattern repeats on a yearly, monthly, or weekly period. | SARIMAX extends the seasonal ARIMA (Box-Jenkins) model by adding exogenous explanatory variables, so it can capture the effect of holidays, economic indicators, or policy variables on a time series. It combines non-seasonal and seasonal autoregressive and moving-average dynamics with external regressors, and is estimated by maximum likelihood in state-space form. |
| ScholarGateJeu de données ↗ |
|
|