Course information

  • Credits: 9
  • Asynchronous teaching
  • Discussion Meeting on Zoom: Th: 12:00pm - 1:15pm
  • Course information sheet. Course outline

References

Books:

  • Markov chains and stochastic stability by Sean Meyn and Richard Tweedie online book
  • Handbook of Markov chain Monte Carlo website
  • Monte Carlo statistical methods by Robert and Casella website

Papers:

  • General state space Markov chains and MCMC algorithms by Roberts and Rosenthal paper
  • Understanding the Metropolis-Hastings algorithm by Chib and Greenberg paper
  • Hastings algorithm at Fifty by Dunson and Johndrow paper
  • Practical Markov Chain Monte Carlo paper
  • A Short History of Markov Chain Monte Carlo paper

Charlie Geyer’s resources:

  • Charlie Geyer’s comprehensive course notes link
  • Charlie Geyer’s shorter MCMC notes link
  • Introduction to MCMC (book chapter) link

Week 0 (Review on your own)

  • Basic introduction to measure theory (Section 2 here) link
  • Introduction to accept-reject link
  • Introduction to R - 1 link
  • Introduction to R - 2 link