Required:
- A First Course in Bayesian Statistical Methods by Peter D. Hoff.:
- Section 9.1: The linear regression model
- Section 9.2: Bayesian estimation for a regression model
- Section 9.3: Model selection
- Section 9.4: Discussion and further references
Optional:
- Bayesian Data Analysis (Third Edition) by Andrew Gelman, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin.:
- Section 14.1: Conditional modeling
- Section 14.2: Bayesian analysis of the classical regression model
- Section 14.4: Goals of regression analysis
- Section 14.5: Assembling the matrix of explanatory variables
- Section 14.6: Regularization and dimension reduction for multiple predictors
- Section 14.7: Unequal variances and correlations