The Statistics Department has several groups involved in cutting edge research.

The Bayesian and Monte Carlo Methods group has research interests encompassing simulation via trans-dimensional Markov chains, sampling algorithms, and stochastic simulation in the absence of likelihoods. Members of the Biostatistics and Ecology group focus on the development, application and evaluation of novel statistical methods for the applied sciences, particularly for medicine and ecology. Research within the Finance and Risk Analysis group includes pricing and hedging of financial derivatives, risk modelling, and valuation. Our Nonparametric Statistics group's strengths include wavelet methods in non-parametric inference, Edgeworth and Saddlepoint approximations, non-parametric binary regression, and functional data analysis. The Stochastic Analysis group is mainly concerned with mathematical and statistical modelling of systems evolving randomly in space and time.

The Department has a solid record for attracting external research support.

Research in Statistics