8th Summer Institute in Statistics and Modeling in Infectious Diseases

Module 7: MCMC I for Infectious Diseases

Week 1, Session 2, Wednesday 1:30 PM - Friday 5:00 PM: Wed Jul 13 to Fri Jul 15

This module is an introduction to Markov chain Monte Carlo (MCMC) methods. The first half of the course includes a general introduction to Bayesian statistics, Monte Carlo, and MCMC. Some relevant facts from the Markov chain theory are reviewed. Algorithms include Gibbs sampling and Metropolis-Hastings. A practical introduction to convergence diagnostics is included. Motivating practical examples progress from generic toy problems to infectious disease applications, which include chain-binomial and general epidemic models. Programming will be in R. Prior familiarity with R would be helpful. Individuals already familiar with MCMC methods and knowledge of R programming should consider MCMC II. It assumes the material in Module 1.