Computational Bayesian Methods Using Brms in R (Virtual Course)
In recent years, Bayesian methods have come to be widely adopted in all areas of science. This is in large part due to the development of sophisticated software for probabilisic programming; a recent example is the astonishing computing capability afforded by the language Stan (mc-stan.org). However, the underlying theory needed to use this software sensibly is often inaccessible because end-users don’t necessarily have the statistical and mathematical background to read the primary textbooks (such as Gelman et al’s classic Bayesian data analysis, 3rd edition). This course provides a relatively accessible and technically non-demanding introduction to the basic workflow for fitting different kinds of linear models using a powerful front-end R package for Stan called brms. Due to the COVID-19 outbreak, this course will be held online.
INSTRUCTOR: Prof. Bruno Nicenboim (Tilburg University, NL).