Comparer des méthodes

	Modèle SARIMA bayésien	Modèle SARIMA
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1970s–1990s	1970 (first edition); 1976 (revised)
Auteur d'origine	Box & Jenkins (classical SARIMA); Bayesian extensions developed through Zellner, Geweke, and later MCMC-era researchers	Box, Jenkins, and Reinsel
Type	Bayesian time-series model	Seasonal time series model
Source fondatrice	Box, G. E. P., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021	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	Bayesian SARIMA, Bayesian seasonal ARIMA, BSARIMA, Bayesian seasonal time-series model	SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component
Apparentées	4	5
Résumé	The Bayesian SARIMA model combines the classical Box-Jenkins Seasonal ARIMA framework with Bayesian inference to handle seasonal time-series data. Rather than producing a single point estimate, it yields a full posterior distribution over model parameters, propagating parameter uncertainty directly into forecasts and enabling principled incorporation of prior knowledge.	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.