Võrdle meetodeid

	Bayes'i Autoregresseeruv (AR) mudel	Bayesian VAR-mudel (BVAR)
Valdkond	Ökonomeetria	Ökonomeetria
Perekond	Regression model	Regression model
Tekkeaasta	1971	1984
Looja	Arnold Zellner; foundational Bayesian time-series work by West & Harrison	Doan, Litterman & Sims
Tüüp	Bayesian time-series model	Multivariate time-series model
Algallikas	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.
Rööpnimetused	Bayesian autoregressive model, BAR model, Bayesian AR, Bayesian time-series autoregression	BVAR, Bayesian VAR, Bayesian vector autoregressive model, BVAR model
Seotud	6	5
Kokkuvõte	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.