Visualization in Bayesian Workflow

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

doi:10.1111/rssa.12378

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.

Keywords

WorkflowVisualizationComputer scienceBayesian probabilityData scienceData miningArtificial intelligenceDatabase

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Publication Info

Year: 2019
Type: article
Volume: 182
Issue: 2
Pages: 389-402
Citations: 1033
Access: Closed

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APA Style

                            
                                
                                    Jonah Gabry, 
                                
                                    Daniel Simpson, 
                                
                                    Aki Vehtari
                                
                                et al.
                            
                            (2019). 
                            Visualization in Bayesian Workflow. 
                            Journal of the Royal Statistical Society Series A (Statistics in Society)
                            , 182
                            (2)
                            , 389-402.
                            https://doi.org/10.1111/rssa.12378
                        

Identifiers

DOI: 10.1111/rssa.12378