Visualization in Bayesian workflow
Methodology
2019-01-31 v5 Applications
Abstract
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.
Cite
@article{arxiv.1709.01449,
title = {Visualization in Bayesian workflow},
author = {Jonah Gabry and Daniel Simpson and Aki Vehtari and Michael Betancourt and Andrew Gelman},
journal= {arXiv preprint arXiv:1709.01449},
year = {2019}
}
Comments
17 pages, 11 Figures. Includes supplementary material