Normal Linear Regression, General Linear Models and Log‐Linear Models

This chapter contains sections titled: The context for Bayesian regression methods The normal linear regression model Normal linear regression: variable and model selection, outlier detection and error form Bayesian ridge priors for multicollinearity General linear models Binary and binomial regression Latent data sampling for binary regression Poisson regression Multivariate responses Exercises References