Visualization in Bayesian workflow
Visualization in Bayesian workflow
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DOI：
10.1111/rssa.12378
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发表时间：
2019-02-01
影响因子：
2
通讯作者：
Gelman, Andrew
中科院分区：
文献类型：
--
作者：
Gabry, Jonah;Simpson, Daniel;Gelman, Andrew
贝叶斯数据分析不仅仅是计算后验分布，贝叶斯可视化也不仅仅是马尔可夫链的轨迹图。实用的贝叶斯数据分析就像所有的数据分析一样，是一个模型建立、推理、模型检验和评估以及模型扩展的迭代过程。可视化在贝叶斯工作流程的每个阶段都是有帮助的，当从应用研究人员使用的现代高维模型类型中进行推断时，可视化是必不可少的。
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.