General Theory and Methodology

Theme Overview

The research carried out under this theme covers foundational and theoretical aspects of probability and inferential statistics, and generic statistical methodology. Current research interests include:

  • Philosophical foundations of probability and statistics
  • Theory of inference, including Bayesian theory, predictive inference and asymptotic theory
  • Core Bayesian methodology
  • Statistical methodology for causal inference
  • Inference for stochastic models, nonparametric and semiparametric inference
  • Methodology for multivariate data, including cluster analysis, multivariate calibration and classification
  • Machine learning, classification, pattern recognition
  • Decision analysis via operational research and financial methods

Theme members

Name Keywords
Christian Henning (Theme Lead) Classification; cluster analysis; foundations of statistics; model selection; multivariate data analysis; robust statistics
Gianluca Baio
Bayesian analysis; causal inference from observational data; evaluation of interventions
Simon Byrne
Bayesian theory; graphical models; probabilistic scoring rules
Richard Chandler
Climatology; environmental sciences; estimating functions; hydrology; inference for dependent data
Codina Cotar
Optimal transport; random graphs; reinforced random walks; statistical mechanics
Petros Dellaportas
Bayesian model choice; graphical models; theory of MCMC
Tom Fearn
Bayesian methods; calibration; classification; multivariate analysis; near infrared spectroscopy
Simon Harden
Foundations, inference
Ioannis Kosmidis Categorical data models; clustering methods; modelling of natural disasters; modelling of sport and health tracking and monitoring data; penalized likelihood methods
Giampiero Marra
Penalised likelihood; microeconomics; splines; simultaneous equation systems; social sciences; unobserved confouding
Sofia Olhede
Ecology; medical imaging; oceanography; penalised likelihood
Gareth Peters Alpha stable processes; copula dependent processes; fractional stable processes; levy processes
Yvo Pokern
High-dimensional Gaussian Markov random fields; inference for partially observed and hypoelliptic diffusion processes; nonparametric inference for stochastic differential equations; sequential Monte Carlo methods
Matina Rassias
Stochastic analysis
Afzal Siddiqui
Energy economics; game theory; optimisation; real options
Jinghao Xue  Hybrid discriminative-generative classification; imbalance learning; partially-supervised learning; statistical pattern recognition

Other members: Elinor JonesFranz Király.

Some of our current PhD students are also working on topics related to this theme.

Current and Recent Externally Funded Projects

  • Statistical modelling and estimation for spatiotemporal data with oceanographic applications, €294k, EU FP7 626775, Apr 2014 - Mar 2017, PI: Olhede.
  • Characterizing Interactions Across Large-Scale Point Process Populations, £152k, EPSRC EP/L001519/1, Jul 2013 - Jun 2015, PI: Olhede.
  • A multicriterion approach for cluster validation, £98k, EPSRC EP/K033972/1, Jun 2013 - May 2017, PI: Hennig.
  • Information geometry for Bayesian hierarchical models, £238k, EPSRC EP/K005723/1, Mar 2013 - Mar 2016, PI: Byrne.
  • Probability, Uncertainty and Risk in the Natural Environment, £683k, NERC NE/J017434/1, Aug 2012 - Aug 2016, PI: Chandler.
  • Semiparametric Sample Selection Modelswith Applications in Biostatistics, Economics and Environmetrics, £100k, EPSRC EP/J006742/1, May 2012 - Jun 2013, PI: Marra.
  • High Dimensional Models for Multivariate Time Series Analysis, £990k, EPSRC EP/I005250/1, Oct 2010 - Sep 2015, PI: Olhede.
  • EnRiMa - Engergy and Risk Management in Public Buildings, €3500k, EC FP7 260041, Oct 2010 - Mar 2014, CI: Siddiqui.