Regression modelEconometrics / time series
Bayesian Autoregressive (AR) Model
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.
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Sources
- Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley. ISBN: 978-0471169376
- West, M., & Harrison, J. (1997). Bayesian Forecasting and Dynamic Models (2nd ed.). Springer. ISBN: 978-0387947259