Bandingkan kaedah

	Model SARIMA	Model ARMA (Autoregresif Moving Average)
Bidang	Ekonometrik	Ekonometrik
Keluarga	Regression model	Regression model
Tahun asal	1970 (first edition); 1976 (revised)	1970
Pengasas	Box, Jenkins, and Reinsel	George E. P. Box and Gwilym M. Jenkins
Jenis	Seasonal time series model	Time series model
Sumber perintis	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)
Berkaitan	5	5
Ringkasan	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.