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
|Christian Hennig (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|
|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|
|Giampiero Marra*||Penalised likelihood; microeconomics; splines; simultaneous equation systems; social sciences; unobserved confouding|
|Sofia Olhede*||Ecology; medical imaging; oceanography; penalised likelihood|
|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|
*These theme members are currently accepting applications for PhD supervision
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.