Methoden vergleichen

	Bayesian Autoregressive (AR) Modell	ARMA-Modell (Autoregressiver gleitender Durchschnitt)
Fachgebiet	Ökonometrie	Ökonometrie
Familie	Regression model	Regression model
Entstehungsjahr	1971	1970
Urheber	Arnold Zellner; foundational Bayesian time-series work by West & Harrison	George E. P. Box and Gwilym M. Jenkins
Typ	Bayesian time-series model	Time series model
Wegweisende Quelle	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.
Aliasnamen	Bayesian autoregressive model, BAR model, Bayesian AR, Bayesian time-series autoregression	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
Verwandt	6	5
Zusammenfassung	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.