Comparer des méthodes

	Test de racine unitaire Augmented Dickey-Fuller (ADF)	Modèle ARIMA (Modèle Autorégressif Intégré à Moyenne Mobile)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1979–1984	1970
Auteur d'origine	Said & Dickey (1984); building on Dickey & Fuller (1979)	George Box and Gwilym Jenkins
Type	Hypothesis test (unit root)	Time series forecasting model
Source fondatrice	Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599–607.	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
Alias	ADF test, ADF unit root test, Dickey-Fuller test (augmented), Said-Dickey test	ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
Apparentées	5	6
Résumé	The Augmented Dickey-Fuller test is the standard procedure for determining whether a univariate time series contains a unit root — that is, whether the series is non-stationary. It extends the original Dickey-Fuller test by including lagged difference terms that absorb serial correlation in the residuals, making the test valid for a wide range of time-series processes encountered in economics and finance.	The ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics.