השוואת שיטות

	מודל ARIMA בייסיאני	Autoregression Vector (VAR)
תחום	אקונומטריקה	אקונומטריקה
משפחה	Regression model	Regression model
שנת המקור	1970s (ARIMA); Bayesian extension prominent from 1990s	1980
הוגה השיטה	Pole, West & Harrison (Bayesian treatment); Box & Jenkins (ARIMA foundation)	Christopher A. Sims
סוג	Bayesian time series model	Multivariate time-series model
מקור מכונן	Pole, A., West, M., & Harrison, J. (1994). Applied Bayesian Forecasting and Time Series Analysis. Chapman & Hall. ISBN: 978-0412416903	Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48.
כינויים	Bayesian ARIMA, BARIMA, Bayesian Box-Jenkins model, Bayesian integrated time series model	VAR, VAR model, vector autoregressive model, multivariate autoregression
קשורות	6	5
תקציר	The Bayesian ARIMA model combines the classical Box-Jenkins ARIMA framework with Bayesian inference. Instead of obtaining single point estimates for autoregressive and moving average parameters, it places prior distributions over them and uses observed data to update beliefs into a full posterior distribution, enabling coherent uncertainty quantification and probabilistic forecasting.	Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.