方法对比

	贝叶斯自回归滑动平均模型	向量自回归 (VAR)
领域	计量经济学	计量经济学
方法族	Regression model	Regression model
起源年份	1970s–1980s	1980
提出者	Box & Jenkins (classical ARMA); Bayesian treatment developed through work of Zellner, Geweke, and others in 1970s–1980s	Christopher A. Sims
类型	Bayesian time series model	Multivariate time-series model
开创性文献	Geweke, J., & Meese, R. (1981). Estimating regression models of finite but unknown order. International Economic Review, 22(1), 55–70.	Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48.
别名	Bayesian ARMA, B-ARMA, Bayesian autoregressive moving average, ARMA with Bayesian inference	VAR, VAR model, vector autoregressive model, multivariate autoregression
相关	6	5
摘要	The 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.	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.