Bayesian Workflow
by Andrew Gelman, Aki Vehtari, Richard Mcelreath, Daniel Simpson, Charles C. Margossian, Yuling Yao, Lauren Kennedy, Jonah Gabry, Paul-Christian Bürkner, Martin Modrák, Vianey Leos Barajas
Bayesian Workflow explores the practical process of Bayesian statistical analysis. With contributions from a broad group of authors in statistics and data analysis, it offers a structured perspective on developing, evaluating, and communicating statistical models for readers studying or applying Bayesian methods.
About This Book
Bayesian Workflow is a book about applying Bayesian methods in a structured and thoughtful way.
It focuses on the workflow surrounding statistical modeling, from developing models to assessing and communicating results.
The book is authored by Andrew Gelman, Aki Vehtari, Richard Mcelreath, Daniel Simpson, Charles C. Margossian, Yuling Yao, Lauren Kennedy, Jonah Gabry, Paul-Christian Bürkner, Martin Modrák, and Vianey Leos Barajas.
It is suited to readers interested in Bayesian statistics, data analysis, and the practical process of statistical modeling.
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