I will post lecture slides here. The Rnw files can be found here.

Slides

Hierarchical

• Shrinkage priors
• Hierarchical models
• Bayesian model selection
• Bayesian model averaging
• Hamiltonian Monte Carlo

State-space models

• Dynamic linear models
  • Kalman Filter and Smoother
  • Polynomial Trend Models
  • Seasonal Models
  • Dynamic Regression
  • Multivariate DLMs
  • Unknown fixed parameters in DLMs
• Hidden Markov models
• Sequential Monte Carlo

Spatial models

• GPs and CARs

Slice sampling and ARMS

• Slice
• ARMS

Bayesian nonparametrics (BNP)

• Finite mixture models (not really BNP)
• Dirichlet process

Other topics

• Approximate Bayesian computation