The importance of step size for Random Walk Metropolis

This video illustrates the importance of choosing appropriate step sizes for each of the parameters in random walk Metropolis. In particular, I focus on how choosing a step size that is too small or large results in slow convergence to the posterior.

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