Lecture 31 Bayesian Regression and Variable Selection (Part A)

Linear regression models; Classical estimators, MLE estimator, likelihood, T-statistic; First level prior analysis, Conjugate priors, Conditional and marginal posteriors, Ridge regression, Predictive distribution, Influence of the conjugate prior; First level prior analysis – Zellner’s G-Prior, Posterior and predictive modeling, Credible HPD regions, Marginal likelihood, Bayes factors and Variable selection.