Visualization in Bayesian workflow

Jonah Gabry*, Daniel Simpson, Aki Vehtari, Michael Betancourt, Andrew Gelman

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

128 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)389-402
Number of pages14
JournalJournal of the Royal Statistical Society. Series A: Statistics in Society
Volume182
Issue number2
DOIs
Publication statusPublished - 1 Feb 2019
MoE publication typeA1 Journal article-refereed

Keywords

  • Bayesian data analysis
  • Statistical graphics
  • Statistical workflow

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