Dr Pam Davy
- Telecommunications traffic modelling
- Data mining
- Computational finance
- Spatial statistics
Professor Ray Chambers
Sample Survey Design and Analysis; Robust Statistical Methods; Graphical Methods in Statistics; Computer Intensive Statistical Methods; Statistical Modelling and Inference; Longitudinal Data Analysis; Analysis of Computer-Linked Data
Dr Robert Clark
- Survey methodology, including design, estimation and analysis
- Household surveys
- Modelling the complex dependencies between observations that arise in many surveys, administrative datasets and observational studies
Professor David Griffiths
- Epidemiology and public health applications of statistics
- Statistics education
- Secondary interests covering quality management, inference, statistical graphics and the history of statistics.
Dr Chandra Gulati
- Statistical decision theory
- Time series / cointegration
- Statistical quality control
Associate Professor Yan-Xia Lin
- The theory of Inference on stochastic processes
- The quasi-likelihood method and its applications
- The theory of stochastic analysis and its applications in finance
- Time series analysis
- Long-memory processes
- Cointegration analysis and its applications
- GARCH models and GARCH-X models
- Mathematics Finance
- Bioinformatics
- Confidential data
- Survey methodology
Dr Anne Porter
- Statistical education. Areas researched include:
- development of flexible teaching and learning strategies (e.g. use of online resource base, delivery via WebtCT.
- development of curriculum and pedagogical practices
- analysis of theoretical and methodological perspectives regarding the nature of teaching and learning in relation to Statistics (e.g. use of reflective practice, experiential learning techniques)
- integration of generic skills into teaching and learning of statistics.
- Applied statistics. These projects emanate from consultancy work. To date these include studies in sport, education and health.
- Sample surveys in particular internet surveys (security, representativeness, modes of production etc).
Associate Professor Ken Russell
Design and analysis of statistical experiments
The design of a statistical experiment involves planning the layout of the experiment; for example, how the treatments will be applied to the experimental units so as to maximise the information obtained and to minimise the interference which can come from systematic variation in the experimental medium. Currently in the design of row-column designs (where systematic variation occurs in two "orthogonal" directions), the design of carry-over experiments (where a sequence of treatments is administered to each unit, and there can be carry-over effects from one treatment application to the next), and in the design of experiments when the classical assumptions about the distribution of the data are not met.
Professor David Steel
- Analysis of aggregate data and ecological inference
- A general method for analyzing social data for modifiable geographical areas
- Estimation and inference for household surveys
- Combining aggregate data and unit record
- Innovations with area level
- Sample survey design, analysis and methodology.
Professor Matt Wand
Matt Wand is chiefly interested in the development of statistical methodology for finding useful structure in large multivariate data sets.
Currently, Matt's specific interests include: generalisd linear mixed models, semiparametric regression, spatial statistics, multivariate density estimation and feature significance, support vector machines and statistical methods for flow cytometric data.
He is also very interested in Statistical Computing and contributes to the field's main software repository - the `Comprehensive R Archive Network'.
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