Bob’s bees: the importance of using multiple bees (chains) to judge MCMC convergence
This video uses an analogy (the release of bees in a house of unknown shape) to convey the importance of using multiple Markov chains to judge convergence to a target distribution in MCMC routines.
Gelman and Rubin's article I refer to is "Inference from Iterative Simulation Using Multiple Sequences", Statistical Science, 1992, and is available from Project Euclid here: https://projecteuclid.org/download/pd....
This video is part of a lecture course which closely follows the material covered in the book, "A Student's Guide to Bayesian Statistics", published by Sage, which is available to order on Amazon here: https://www.amazon.co.uk/Students-Gui...
For more information on all things Bayesian, have a look at: https://ben-lambert.com/bayesian/. The playlist for the lecture course is here: • A Student's Guide to Bayesian Statistics