"Introduction to Bayesian Analysis and MCMC" is aimed at statisticians who are thinking of taking the second course on spatial statistics but would like to go through a preparatory course providing a gentle introduction with a large practical component.
The first short-course on "Bayesian Modelling and Computation" is aimed at applied scientists who are thinking of using Bayesian methods and would like to receive a gentle introduction with a large practical component.
No previous knowledge of Bayesian methods is necessary. However, some familiarity with standard probability distributions (normal, binomial, Poisson, gamma) and standard statistical methods such as multiple regression will be assumed.
Theory lectures on the Bayes theorem, elements of Bayesian inference, choice of prior distributions and introduction to MCMC will be followed by hands-on experience using R and the WinBUGS software. Some of the data analysis examples discussed here will be enhanced by using spatial statistics methods in the second course.
More advanced methods using Hamiltonian MCMC, reversible jump, INLA, Variational Bayes, and ABC will also be introduced.
On the first day, the course will start with registration and coffee at 9.00am with formal teaching starting at 9.30 am On the last day, formal teaching will end at about 5.00pm. Afterwards there will be an opportunity for participants to ask questions about the course.
Southampton Statistical Sciences Research Institute
Building 39, University of Southampton
Southampton
SO17 1BJ
Prof Sujit K Sahu
1st -2nd June 2015
£60 for DTC students
£200 for registered students
£250 for staff from academic institutions (including research centres)
£300 for all other participants
The course fee includes course materials, lunches and morning and afternoon refreshments. Travel and accommodation are to be arranged and paid for by the participant.