Sample Topics in a Two-Day Course on Bayesian Methods

Day 1

  • Introduction to the BVAR and a standard Gibbs sampler to simulate coefficients.

  • The Minnesota prior.

  • Hierarchical shrinkage with Bayesian Lasso priors.

  • Stochastic Search Variable Selection (SSVS) using large variance--small variance mixture priors.

Day 2

  • SSVS with large variance--zero variance mixtures, i.e. spike-slab priors.

  • Time-varying parameter VARs.

  • Shrinking time-varying coefficients to fixed coefficients: stochastic model specification search (SMSS).

  • Bayesian VARMAs.