Module 7.3: The Metropolis-Hastings algorithm

Required:

• A First Course in Bayesian Statistical Methods by Peter D. Hoff.:
  • Section 10.4: Metropolis, Metropolis-Hastings and Gibbs
  • Section 10.5: Combining the Metropolis and Gibbs algorithm
  • Section 10.6: 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 11.2: Metropolis and Metropolis-Hastings algorithms
  • Section 11.3: Using Gibbs and Metropolis as building blocks