Applied Bayesian Analysis

Catalog description

Bayesian data analysis with emphasis on application and computation using R or similar software. Topics include: probability models, prior distributions, Bayes theorem, single parameter models, posterior predictive distribution, Gibbs sampling, MCMC simulations, regression models, generalized linear models, hierarchical models, model checking and diagnostics.