Introduction to Bayesian Linear Models
Abstract
In this lecture we will introduce Bayesian estimation for linear models using the Normal-Gamma conjugate prior.
Readings: Christensen Chapter 2 and Chapter 6, Appendix A & B as needed C
In this lecture we will introduce the Bayesian perspective for estimation in linear models. We will start with the Conjugate Normal-Gamma prior and show that the posterior is in the same family. This induces marginal distributions that are (multivariate) Student-t for any linear combination of the parameters $\beta$.
