Visualization in Bayesian Workflow
本文探讨可视化在贝叶斯数据分析工作流各阶段（模型构建、推断、检查与评估、扩展）中的作用，强调其对现代高维模型推断不可或缺。
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.