Porównaj metody

	Model Autoregresywny (AR)	Model ARMA (Autoregresyjny Model Średniej Ruchomej)
Dziedzina	Ekonometria	Ekonometria
Rodzina	Regression model	Regression model
Rok powstania	1970s (popularised 1976)	1970
Twórca	George E. P. Box and Gwilym M. Jenkins	George E. P. Box and Gwilym M. Jenkins
Typ	Time series model	Time series model
Źródło pierwotne	Box, G. E. P., & Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0816211043	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
Inne nazwy	AR model, AR(p) model, autoregression, AR process	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
Pokrewne	6	5
Podsumowanie	An autoregressive model of order p — AR(p) — expresses the current value of a time series as a linear function of its own p most recent past values plus a white-noise error. It is the building block of the Box-Jenkins family of time-series models and is widely used for forecasting stationary economic and financial series.	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.