Visualization in Bayesian Workflow
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 15, 2019
- Source ID
- 10.1111/rssa.12378
Entities
People
- Aki Vehtari
- Andrew Gelman
- Daniel Simpson
- Jonah Gabry
- Michael Betancourt
Organizations
- Aalto University
- Alfred P. Sloan Foundation
- Columbia University
- Defense Advanced Research Projects Agency
- Institute of Education Sciences
- National Science Foundation
- Office of Naval Research
- University of Toronto