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Bayesov autoregresivni (AR) model×Model ARMA (Autoregresivni pokretni prosjek)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka19711970
TvoracArnold Zellner; foundational Bayesian time-series work by West & HarrisonGeorge E. P. Box and Gwilym M. Jenkins
VrstaBayesian time-series modelTime series model
Temeljni izvorZellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley. ISBN: 978-0471169376Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗
Drugi naziviBayesian autoregressive model, BAR model, Bayesian AR, Bayesian time-series autoregressionARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
Srodne65
SažetakThe Bayesian AR model estimates an autoregressive time-series process by combining a likelihood derived from the AR structure with prior distributions over the lag coefficients and error variance. Rather than producing single point estimates, it yields full posterior distributions, enabling principled uncertainty quantification and probabilistic forecasting.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.
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ScholarGateUsporedite metode: Bayesian AR model · ARMA model. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare