Autoregression overview

Model:

\[ y_t \sim \text{normal}(\mu_t, \sigma) \]

\[ \mu_t = \phi \cdot y_{t-p, \dots, t-1} \]

Parameters needing priors:

• \(\phi\) (lag weights)
• \(\sigma\) (observation model standard deviation)

Data:

• \(y\) (continuous outcome)
• \(X\) (predictors)