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Bayesov SARIMA model×ARIMA model (Autoregressive Integrated Moving Average)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka1970s–1990s1970
TvoracBox & Jenkins (classical SARIMA); Bayesian extensions developed through Zellner, Geweke, and later MCMC-era researchersGeorge Box and Gwilym Jenkins
VrstaBayesian time-series modelTime series forecasting model
Temeljni izvorBox, G. E. P., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗
Drugi naziviBayesian SARIMA, Bayesian seasonal ARIMA, BSARIMA, Bayesian seasonal time-series modelARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
Srodne46
SažetakThe 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.The ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics.
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ScholarGateUsporedite metode: Bayesian SARIMA Model · ARIMA model. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare