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Bayesijanski ARMA model×Model ARMA (Autoregresivni pokretni prosjek)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka1970s–1980s1970
TvoracBox & Jenkins (classical ARMA); Bayesian treatment developed through work of Zellner, Geweke, and others in 1970s–1980sGeorge E. P. Box and Gwilym M. Jenkins
VrstaBayesian time series modelTime series model
Temeljni izvorGeweke, J., & Meese, R. (1981). Estimating regression models of finite but unknown order. International Economic Review, 22(1), 55–70. link ↗Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗
Drugi naziviBayesian ARMA, B-ARMA, Bayesian autoregressive moving average, ARMA with Bayesian inferenceARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
Srodne65
SažetakThe Bayesian ARMA model applies Bayesian inference to the classical autoregressive moving average framework for stationary univariate time series. Rather than producing single point estimates for the AR and MA parameters, it yields full posterior distributions, naturally incorporating prior knowledge and providing coherent uncertainty quantification over forecasts and impulse responses.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 ARMA model · ARMA model. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare