Bayesian Statistics
Research Groups
- Actuarial and Financial Mathematics
- Applied Algebra and Information Theory
- Bayesian Statistics
- Computational Mathematics and High-Performance Computing
- Enumerative Combinatorics
- Fluid Dynamics
- Functional Analysis
- Mathematics Education
- Matrix Analysis
- Number Theory
- Potential Theory
- Probability
- Quantum Information and Computation
- Real Algebra
- Relativity and Mathematical Physics
- Statistical Genetics and Bioinformatics
- Statistical Modelling
Bayesian Statistics
Bayesian statistics is perhaps the oldest branch of statistics, tracing its roots to a paper from 1763 by a Presbyterian minister named Thomas Bayes. The method he came up with allows for the accumulation of information via a simple formula involving probability distributions.
Unfortunately putting the method into practice was hard because, whilst the formula was simple, the calculations involved for real world data sets were too taxing for pen-and-paper mathematicians. With the increase in computer power in the second half of the 20th century it finally became possible to use Bayes’ theorem. It has now become one of the most popular tools for probabilistic analysis, and has found particular favour as part of the big data and artificial intelligence revolution of the early 21st century.
Applications of Bayesian statistics are found in medical statistics and bioinformatics, manufacturing analytics, forecasting, machine learning and artificial intelligence, climate change, social network analysis and many other areas.
The group at UCD contains some of the world’s leading practitioners and proponents of Bayesian statistics with particular expertise in topics such as cluster analysis, model choice, model fitting, stochastic processes, and latent variable modelling. Bayesian statistics forms a core component of the Science Foundation Ireland funded Insight Centre for Data Analytics.
People
Prof. Nial Friel
Research Interests: Bayesian Statistics, Statistical Network Analysis, Monte Carlo Methods
(opens in a new window)Prof. Brendan Murphy
Research Interests: Clustering, Classification and Network Analysis
(opens in a new window)Dr Michael Fop
Research Interests : Clustering and Classification, High-Dimensional Data Analysis, Statistical Modelling, Statistical Network Analysis
Dr Isabella Gollini
Research Interests :Statistical models, bayesian statistics, fast inferential approaches, statistical network analysis
(opens in a new window)Dr Claire Gormley
Research Interests: Statistical Methodology, Bayesian Methods, Applied Statistics
(opens in a new window)Dr Garrett Greene
Research Interests:Statistical modelling, medical statistics, classification problems, model selection and regularisation.
(opens in a new window)Dr Riccardo Rastelli
Research Interests: Statistical modelling, computational statistics, statistical network analysis.
Dr Michael Salter-Townshend
Research Interests :Bayesian Statistics, Statistical Modelling, Statistical Genetics
Group Contact (Email): (opens in a new window)Prof Nial Friel