BUC2: `Big data: thinking globally’
BUC2 will take place at UNAM on 22-24th February 2016. It will include a PhD conference, with participants from Bath and UNAM, and a short-course centred around dealing with big data, both in terms of statistical techniques and the challenges associated with computation.
Dr Gavin Shaddick
Dr Daniel Simpson
Dr Karim Anaya- Izquierdo,
Department of Mathematical Sciences, University of Bath, United Kingdom
This course provides an introduction to modelling relationships in both space and time with particular focus on fitting complex models to big data. The course will cover both theory and applied examples, the latter specifically through practical ‘hands-on’ computer sessions in which participants will be guided through the analyses of real data with both temporal and spatial structure.
- The need for spatial and temporal modelling and the role of big data
- Bayesian computation
- Regional modelling with big data
- Scalable spatial modelling
- Extending models to further dimensions
Teaching methods & Course format:
- A mixture of lectures, worked examples and computer-based practicals.
- Students will need to bring a laptop to the course with R and R-INLA software installed (details of how to access these materials will be provided on registration)
- An understanding of the basic principles of hierarchical Bayesian modelling
- An understanding of the need to account for spatial and temporal dependence in environmental research and, more generally, when modelling complex systems
- Knowledge of how how integrated nested Laplace approximations (INLA) can be used to implement methods for spatial and temporal modelling with high-dimensional data within a Bayesian framework
Spatio-Temporal Methods in Environmental Epidemiology
Gavin Shaddick and James V. Zidek, Chapman and Hall/CRC
For further information
Please contact Gavin Shaddick, email@example.com