The Department of Statistics' research is concentrated in three key areas; time series analysis, risk and stochastics and social statistics.

The Department's research in time series encompasses many aspects of the discipline. We are keenly involved in both theoretical developments and practical applications. Current areas of interest include non-parametric inference for financial time series, model error in forecasting non-linear systems, structural modelling of weather series and decision support using weather and climate models. The Centre for the Analysis of Time Series (CATS) is affiliated with the department.

Our research in risk and stochastics covers risk theory and other related aspects in general insurance as well as life insurance topics. Research in financial mathematics is on the pricing of options, including exotic (look-back) options. We are also doing research on models with jumps and stochastic volatility.

The Department's research in social statistics is of both a theoretical and applied nature with an emphasis on developing statistical methodology for complex data. Current topics include statistical modelling of latent variables, clustered data, measurement error and model choice. Software, making the methods available for applied scientists, is developed and widely used in the social and biomedical sciences.