Bandingkan metode

	Model Autoregresif (AR) Bayesian	Model Vektor Autoregresi Bayesian (BVAR)
Bidang	Ekonometrika	Ekonometrika
Keluarga	Regression model	Regression model
Tahun asal	1971	1984
Pencetus	Arnold Zellner; foundational Bayesian time-series work by West & Harrison	Doan, Litterman & Sims
Tipe	Bayesian time-series model	Multivariate time-series model
Sumber perintis	Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley. ISBN: 978-0471169376	Doan, T., Litterman, R., & Sims, C. (1984). Forecasting and conditional projection using realistic prior distributions. Econometric Reviews, 3(1), 1–100.
Alias	Bayesian autoregressive model, BAR model, Bayesian AR, Bayesian time-series autoregression	BVAR, Bayesian VAR, Bayesian vector autoregressive model, BVAR model
Terkait	6	5
Ringkasan	The 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 Bayesian Vector Autoregression (BVAR) model extends the classical VAR framework by incorporating prior beliefs about the model coefficients. Priors — most commonly the Minnesota prior — shrink VAR coefficients toward economically sensible values, dramatically reducing overfitting and improving out-of-sample forecast accuracy even when the number of variables is large.