Comparer des méthodes

	Modèle SARIMA avec Rupture Structurelle	Modèle SARIMA
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1970s–1998	1970 (first edition); 1976 (revised)
Auteur d'origine	Box & Jenkins (SARIMA); Bai & Perron (structural break detection)	Box, Jenkins, and Reinsel
Type	Time series model with regime shifts	Seasonal time series model
Source fondatrice	Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78.	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	SARIMA with structural breaks, break-augmented SARIMA, piecewise SARIMA, SARIMA-SB	SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component
Apparentées	3	5
Résumé	The Structural Break SARIMA model extends the classical Seasonal ARIMA framework by explicitly detecting and accommodating abrupt, permanent shifts in the level, trend, or seasonal pattern of a time series. Rather than forcing a single SARIMA specification across the entire sample, the model partitions the series at estimated breakpoints and fits separate SARIMA processes to each resulting segment, producing more accurate forecasts and reliable inference in the presence of regime changes.	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.