The Statistics Research Group within the Research School of Finance, Actuarial Studies and Statistics (RSFAS) comprises staff with a broad range of expertise and research interests. Research conducted by members of the group has produced a strong and extensive publication record. The group’s research spans the following areas:
Statistical Theory and Methods including nonparametric and semiparametric methods, functional data analysis, models for spatio-temporal and correlated data, survey analysis, time series analysis, network data modelling and non-Euclidean statistics.
Probability and Stochastic Processes including Lévy processes, stochastic calculus, martingales and Markov processes, diffusion and jump processes, stochastic differential equations, limit theorems, high-dimensional probability and Poisson-Dirichlet distributions.
Data Science including statistical machine learning, high-dimensional statistics, computational methods, data visualisation, statistical software development (particularly R packages), and Bayesian methods.
Applications of probability and statistics in various disciplines, including actuarial science and insurance risk, mathematical finance, agriculture and biometry, biostatistics and bioinformatics, Earth sciences and geophysics, ecological and environmental studies, forensic sciences, social sciences, and other fields.
Much of our research is multidisciplinary, with staff collaborating across the University and with government agencies such as the Mathematical Sciences Institute, School of Computing, Crawford School of Public Policy, National Centre for Epidemiology and Population Health, Research School of Biology, Research School of Earth Sciences, the Statistical Support Network, Department of Agriculture, Fisheries and Forestry, CSIRO, Geoscience Australia, and the Australian Bureau of Statistics.
A distinguishing feature of our research group is the high level of international collaboration among its members, fostered by a vibrant seminar and visitor program and an annual research workshop.
Further information about research interests can be found on the profile pages of the Statistics faculty.
NEWS
Top publications
Congratulations to Francis Hui for his publication in the Journal of the American Statistical Association; and to Jiazhen Xu, Andy Wood and Tao Zou for their publication in Biometrika. Both journals are top Statistics journals.
Associate Editor appointment
Francis Hui was appointed Associate Editor for the journal Biometrics.
Top publications
Yanrong Yang published her paper “Identifying the structure of high-dimensional time series via eigen-analysis” in The Journal of the American Statistical Association and Tao Zou published his paper “Fixed and Random Covariance Regression Analyses” in The Annals of Statistics. These two journals are among the premiere statistics journals in the world!
Recent selected publications
Quasi-Score Matching Estimation for Spatial Autoregressive Model with Random Weights Matrix and Regressors
Liang, X. & Zou, T. (2025) Forthcoming in the Journal of Business & Economic Statistics
Random effects model-based sufficient dimension reduction for independent clustered data
Nghiem, L.H. & Hui, F.K.C. (2025). Forthcoming in the Journal of the American Statistical Association.
Robust functional principal component analysis for non-Euclidean random objects
Xu, J., Wood, A. T. A., & Zou, T. (2025) Biometrika, 2025, asaf040
'Penalized Sparse Covariance Regression with High Dimensional Covariates
Gao, Y., Zhang, Z., Cai, Z., Zhu, X., Zou, T. & Wang, H. (2024), Forthcoming in Journal of Business & Economic Statistics
Identifying the structure of high-dimensional time series via eigen-analysis
Zhang, B., Gao, J., Pan, G., & Yang, Y. (2025). Forthcoming in The Journal of the American Statistical Association