Comparer des méthodes

	Modèle ARMA à paramètres variant dans le temps (TVP-ARMA)	Modèle ARMA (Autoregressive Moving Average)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1976	1970
Auteur d'origine	Cooley & Prescott (1976); further formalised by Harvey (1989)	George E. P. Box and Gwilym M. Jenkins
Type	State-space time series model	Time series model
Source fondatrice	Cooley, T. F., & Prescott, E. C. (1976). Estimation in the presence of stochastic parameter variation. Econometrica, 44(1), 167–184.	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
Alias	TVP-ARMA, time-varying ARMA, state-space ARMA, locally stationary ARMA	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
Apparentées	3	5
Résumé	The time-varying parameter ARMA (TVP-ARMA) model extends the classical ARMA framework by allowing the autoregressive and moving-average coefficients to evolve over time. Embedded in a state-space representation and estimated via the Kalman filter, it captures structural change and parameter instability in time series without requiring an explicit breakpoint.	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.