השוואת שיטות

	מודל ARIMA (Autoregressive Integrated Moving Average)	מבחן שורש יחידה אוגמנטטיבי של דיקי-פולר (ADF)
תחום	אקונומטריקה	אקונומטריקה
משפחה	Regression model	Regression model
שנת המקור	1970	1979–1984
הוגה השיטה	George Box and Gwilym Jenkins	Said & Dickey (1984); building on Dickey & Fuller (1979)
סוג	Time series forecasting model	Hypothesis test (unit root)
מקור מכונן	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.	Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599–607.
כינויים	ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)	ADF test, ADF unit root test, Dickey-Fuller test (augmented), Said-Dickey test
קשורות	6	5
תקציר	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.	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.