In our treatment of Bayesian inference, we focus on practice rather than philosophy. We demonstrate our attitudes via examples that have arisen in the applied research of ourselves and others.

In this note, we describe our own entry in the “inference engine” sweepstakes but, perhaps more importantly, describe the ongoing development of some R packages that perform other aspects of …

We illustrate issues of model construction and computation with a relatively complete Bayesian analysis of an educational experiment and of a meta-analysis of a set of medical studies.

Andrew Gelman Columbia than trace plots of Markov chains. Practical Bayesian data analysis, like all data analysis, is an iterative process of model building, inference, model checking

Solutions to some exercises from Bayesian Data Analysis, third edition, by Gelman, Carlin, Stern, and Rubin 24 June 2019 These solutions are in progress.

exploratory data analysis and Bayesian modeling. I do not think of con idence intervals as inverses of hypothesis tests. Rather, I tend to think of maximum likelihood and other classical estimation …

In this paper, our treatment of Bayesian computation is from a Bayesian software perspective: we limit ourselves to discussing methods that were key for the development of software for Bayesian …

Pro-Bayesian quotes Hox (2002): “In classical statistics, the population parameter has only one specific value, only we happen not to know it. In Bayesian statistics, we consider a probability distribution of …

The data (con-centrations of a compound in blood and exhaled air over time) are only indirectly informative of the indi-vidual level parameters, which refer to equilibrium concentrations, volumes, …

Browne and Draper (2005) review much of the extensive literature in the course of comparing Bayesian and non-Bayesian inference for hierarchical models.