Comparer des méthodes

	Modèle ARMA (Autoregressive Moving Average)	Modèle Moyenne Mobile (MM)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1970	1970
Auteur d'origine	George E. P. Box and Gwilym M. Jenkins	Box and Jenkins
Type	Time series model	Linear time series model
Source fondatrice	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.	Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744
Alias	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)	MA model, MA(q) process, moving-average process, Box-Jenkins MA
Apparentées	5	5
Résumé	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.	The Moving Average model of order q — written MA(q) — expresses the current value of a time series as a linear combination of the current and past random shocks (innovations). Unlike the AR model which uses lagged values of the series itself, the MA model uses lagged error terms, making it well-suited for capturing short-lived disturbances that dissipate over q periods.