Applied probability and theoretical statistics
The Applied Probability and Theoretical Statistics research group is active in the development of new statistical methodologies for inference in stochastic systems, as well as in adapting and extending existing methods and computational algorithms. Primary interests are in developing the theoretical properties of techniques used for both classical and Bayesian statistics and in the study of applied probability models. Particular focus lies in inference procedures for complex data structures, high-dimensional data and non-standard stochastic models. The group is active in advancing the theory and methodology of Monte Carlo methods and is particularly motivated to the development of highly accurate inference methods for a range of applications, including spatial-temporal modelling, mathematical finance and medicine.
Researchers involved
Dr Heather S Battey

Dr Heather S Battey
Lecturer in Statistics
Professor Axel Gandy

Professor Axel Gandy
Chair in Statistics
Dr Nikolas Kantas

Dr Nikolas Kantas
Lecturer in Statistics
Dr Anthea Monod

Dr Anthea Monod
Lecturer in Biomathematics
Professor Guy Nason

Professor Guy Nason
Chair in Statistics
Dr Mikko S Pakkanen

Dr Mikko S Pakkanen
Lecturer in Maths Finance and Stats
Dr Almut Veraart

Dr Almut Veraart
Reader in Statistics
Professor Alastair Young

Professor Alastair Young
Chair in Statistics