Introduction to Bayesian statistics using BUGS
Next course: Tuesday 23rd – Wednesday 24th October 2018
- Day 1 – Introduction to the use of Monte Carlo methods, Bayesian methods, Markov chain Monte Carlo (MCMC), regression models, and implementation in OpenBUGS/WinBUGS or JAGS/OpenBUGS/WinBUGS via R.
- Day 2 – Generalised linear models, predictions, missing data, model criticism, model comparison and assessing sensitivity to prior distributions, introduction to hierarchical models.
See course details for the full timetable.
The emphasis throughout will be on practical examples: software and code to carry out all the analyses will be provided (see software download). Participants are encouraged to bring their own laptops for the practicals.
- Basic probability concepts: discrete and continuous random variables; probability density functions; expectation; variance; familiarity with standard probability distributions (e.g. normal, binomial, uniform).
- A good understanding of classical (ie non-Bayesian) statistical modelling: likelihood (as in maximium likelihood estimation) and sampling distributions; linear regression; generalised linear models including logistic regression; assessment of model fit using residuals.
We also run a companion course Advanced Bayesian Modelling with BUGS.
October 2018 course: Registration form