Confronta i metodi

	Modello SARIMA	Modello ARMA (Autoregressive Moving Average)
Campo	Econometria	Econometria
Famiglia	Regression model	Regression model
Anno di origine	1970 (first edition); 1976 (revised)	1970
Ideatore	Box, Jenkins, and Reinsel	George E. P. Box and Gwilym M. Jenkins
Tipo	Seasonal time series model	Time series model
Fonte seminale	Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
Alias	SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
Correlati	5	5
Sintesi	SARIMA extends ARIMA by adding seasonal autoregressive and moving-average operators to capture repeating patterns at fixed intervals — such as monthly, quarterly, or annual cycles. Denoted SARIMA(p,d,q)(P,D,Q)s, it is the standard workhorse for univariate seasonal time series forecasting in econometrics, economics, and official statistics.	The ARMA(p,q) model describes a stationary time series as a combination of two components: an autoregressive part that regresses the current value on its own past p values, and a moving average part that accounts for past q error terms. It is the foundational framework of the Box-Jenkins methodology for univariate time series modelling and short-run forecasting.