Rafael S. de Souza’s book “Bayesian Models for Astrophysical Data” won the 2018 Prose Award best book of the year in Astronomy and Cosmology. This comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to use directly or adapt. It begins by examining the normal model from both frequentist and Bayesian perspectives, then progresses to a full range of Bayesian generalized linear and mixed or hierarchical models, as well as additional types of models such as ABC and INLA. The book provides code that is largely unavailable elsewhere and includes details on interpreting and evaluating Bayesian models. Initial discussions offer models in synthetic form so that readers can easily adapt them to their own data; later the models are applied to real astronomical data. The consistent focus is on hands-on modeling, analysis of data, and interpretation to address scientific questions. A must-have for astronomers, the book’s concrete approach will also be attractive to researchers in the sciences more broadly.

Rafael is the Chair of the Cosmostatistics Initiative, and his research at UNC focus in developing hierarchical Bayesian models to analyse thermonuclear reaction rates.

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