Taking a look at tidybayes

Matthew Kay will be presenting an overview of his package, tidybayes, an R library that assists with summarizing and presenting results from Bayesian data analysis. Popular packages for Bayesian data analysis such as brms, rstan, rstanarm, etc., each return model results using different formats. The tidybayes package helps standardize model outputs & objects in line with practices used in the tidyverse, enabling better integration with other common workflows in R.

Kay is an assistant professor at the University of Michigan School of Information, as well as the School of Electrical Engineering and Computer Science in the College of Engineering. Kay's research areas focus on personal informatics, the development of statistical tools & visualizations, and communicating statistical uncertainty.

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Pizza and refreshments will be provided (thanks SPARK!), and after the meetup we'll head to a local watering hole (TBD) to continue the conversation.