방법 비교

	베이즈 자기회귀 (AR) 모형	ARMA 모형 (자기회귀 이동평균)
분야	계량경제학	계량경제학
계열	Regression model	Regression model
기원 연도	1971	1970
창시자	Arnold Zellner; foundational Bayesian time-series work by West & Harrison	George E. P. Box and Gwilym M. Jenkins
유형	Bayesian time-series model	Time series model
원전	Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley. ISBN: 978-0471169376	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
별칭	Bayesian autoregressive model, BAR model, Bayesian AR, Bayesian time-series autoregression	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
관련	6	5
요약	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 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.