We will cover the following recipes in this chapter:
- Getting the posterior density in STAN
- Formulating a linear regression model
- Assigning the priors
- Doing MCMC the manual way
- Evaluating convergence with CODA
- Bayesian variable selection
- Using a model for prediction
- GLMs in JAGS