Overview
Topic status: We're looking for students to study this topic.
Modern Bayesian inference and statistical modelling depends on computational techniques for drawing samples from complex hierarchically defined probability models. This project will compare recent innovations in Markov chain Monte Carlo techniques, and explore ways of extending recent advances in modelling autologistic distributions to Potts models and other intractable models. Applications for these techniques are in medical imaging and other areas of spatial statistics.
- Study level
- PhD
- Supervisors
- QUT
- Organisational unit
Science and Engineering Faculty
- Research area
- Contact
- Please contact the supervisor.
