An Intuitive Introduction to Metropolis-Hastings Algorithm Sampling and Diagnostics
Published:
Project Overview
(R and Shiny-based Programming Project)
My first aim in this stochastic models and simulation project was to understand the Metropolis-Hastings algorithm and a few Markov chain Monte Carlo (MCMC) diagnostics at a more intuitive, visual level, using plots that are both animated and interactive. The second was to present that compactly to people who are new to MCMC and to R. Markov chains lend themselves well to animation, since each step depends on the previous one and there are plenty of parameters worth watching evolve.