विधियों की तुलना करें

	बायेसियन ऑटोरेग्रेसिव (AR) मॉडल	बेयसियन ARMA मॉडल
क्षेत्र	अर्थमिति	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	1971	1970s–1980s
प्रवर्तक	Arnold Zellner; foundational Bayesian time-series work by West & Harrison	Box & Jenkins (classical ARMA); Bayesian treatment developed through work of Zellner, Geweke, and others in 1970s–1980s
प्रकार	Bayesian time-series model	Bayesian time series model
मौलिक स्रोत	Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley. ISBN: 978-0471169376	Geweke, J., & Meese, R. (1981). Estimating regression models of finite but unknown order. International Economic Review, 22(1), 55–70.
उपनाम	Bayesian autoregressive model, BAR model, Bayesian AR, Bayesian time-series autoregression	Bayesian ARMA, B-ARMA, Bayesian autoregressive moving average, ARMA with Bayesian inference
संबंधित	6	6
सारांश	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 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.