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Visualization in Bayesian workflow

Author

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  • Jonah Gabry
  • Daniel Simpson
  • Aki Vehtari
  • Michael Betancourt
  • Andrew Gelman

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.

Suggested Citation

  • Jonah Gabry & Daniel Simpson & Aki Vehtari & Michael Betancourt & Andrew Gelman, 2019. "Visualization in Bayesian workflow," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(2), pages 389-402, February.
    • Handle: RePEc:bla:jorssa:v:182:y:2019:i:2:p:389-402
    DOI: 10.1111/rssa.12378
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