https://youtu.be/E8vdXoJId8M
RoyalStatSoc
Speakers: Jonah Gabry - Columbia University, New York Daniel Simpson - University of Toronto
Bayesian data analysis is about more than just computing a posterior distribution, and Bayesian visualization is about more than trace plots of Markov chains. Practical Bayesian data analysis, like all data analysis, is an iterative process of model building, inference, model checking and evaluation, and model expansion. Visualization is helpful in each of these stages of the Bayesian workflow and it is indispensable when drawing inferences from the types of modern, high dimensional models that are used by applied researchers.
