Visualization in Bayesian workflow. (15th January 2019)

• Record Type: Journal Article
• Authors: Gabry, Jonah; Simpson, Daniel; Vehtari, Aki; Betancourt, Michael; Gelman, Andrew
• Is Part Of: Journal of the Royal Statistical Society. Volume 182:Number 2(2019)
• Page Start: 389
• Page End: 402
• Publication Date: 2019-01-15
• Subjects: Bayesian data analysis -- Statistical graphics -- Statistical workflow; Social sciences -- Statistical methods -- Periodicals; Statistics -- Periodicals; 300.15195
• DOI: 10.1111/rssa.12378
• Languages: English
• ISSNs: 0964-1998

Abstract

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.