Comparer des méthodes

	Modèle de Moyenne Mobile Non Linéaire (NMA)	Modèle ARMA (Autoregressive Moving Average)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1978	1970
Auteur d'origine	Granger & Andersen (bilinear/NMA framework); Tong (nonlinear time series theory)	George E. P. Box and Gwilym M. Jenkins
Type	Nonlinear time series model	Time series model
Source fondatrice	Granger, C. W. J., & Andersen, A. P. (1978). An Introduction to Bilinear Time Series Models. Vandenhoeck and Ruprecht, Gottingen.	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
Alias	NMA model, nonlinear moving average, NLMA model, nonlinear MA	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
Apparentées	4	5
Résumé	The Nonlinear Moving Average (NMA) model extends the classical linear MA model by allowing the current observation to depend on past innovations through a nonlinear function rather than a simple weighted sum. It is used in time series analysis when error shocks transmit to outcomes in an asymmetric or state-dependent fashion.	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.