Welcome to the Monte Carlo–Markov Chains Statistical Methods series, where we explore the theory and practice of probabilistic inference and MCMC sampling.

Articles

  1. What is Probability?
  2. Random Variables and Sampling
  3. Monte Carlo Methods
  4. Understanding Markov Chains
  5. Introducing MCMC
  6. The Metropolis Algorithm
  7. The Metropolis-Hastings Algorithm
  8. Gibbs Sampling Explained
  9. Convergence Diagnostics
  10. MCMC in Practice with Python