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General Theory and Methodology


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 Position Selected Applications  Keywords
Christian Hennig Senior Lecturer (Theme Lead) Various, currently including biogeography, musicology, social stratification Cluster analysis, foundations of statistics and data analysis, robust statistics
Gianluca Baio  Lecturer  Evaluation of interventions, with specific interest in health care
Regression discontinuity designs in epidemiology
Richard Chandler Senior Lecturer Climatology, hydrology, environmental sciences
Inference for dependent data, estimating functions
Maria De Iorio
Reader
   
Tom Fearn Professor  Near infrared spectroscopy Multivariate analysis, including distance-based methods, visualisation, classification
Mark Girolami Professor  Bioinformatics, systems biology
Multivariate calibration of nonlinear dynamic systems, theory and methodology
Ioannis Kosmidis Lecturer    Bias reduction, simulation, clustering
Giampiero Marra Lecturer  Socio-economic studies, biostatistics, air pollution
Semiparametric simultaneous equation estimation methods for studies affected by unobservable confounding, heterogeneity
and sample selection  
Sofia Olhede Professor Medical imaging, oceanography, ecology Penalised likelihood
Yvo Pokern Lecturer    Nonparametric estimation for diffusions, hypoelliptic diffusions, numerical aspects of Gaussian Markov Random Fields
Afzal Siddiqui Senior Lecturer  Energy economics, risk management
Real options, optimisation
Jinghao Xue Lecturer  Medical imaging
Pattern recognition, data mining, image processing
Phil Dawid Honorary Professor Evidential reasoning, legal and forensic statistics.
Foundations, causal inference, Bayesian decision-theory, predictive inference, information geometry
Trevor Sweeting Emeritus Professor Various, currently biological and medical applications, information retrieval systems Foundations, Bayesian theory, predictive inference, asymptotic theory
Ben Calderhead Postdoctoral Research Fellow
   
Simon Harden
PhD Student    
Joanna Kaczmarska
PhD Student
   
Xiao M. Ken Liang
PhD Student    
Daniel Meddings PhD Student    
Ying Zhang PhD Student     

Recent research grants

  • 2012-2013. EPSRC. Semiparametric Sample Selection Modelswith Applications in Biostatistics, Economics and Environmetrics (Marra)
  • 2010-2014. European Commission FP7. Energy Efficiency and Risk Management in Public Buildings (EnRiMa).  (Siddiqui, jointly with European collaborators)  
  • 2010-2013.  BBSRC.  Inference-based Modelling in Population and Systems Biology (Girolami)
  • 2008-2011. Mid-Norway Business Research Fund, Statkraft, and Trønder Energi. Financial Engineering Analysis of Electricity Spot and Derivatives Markets (ELDEV).  (Siddiqui, jointly with NTNU and Trondheim Business School)
  • 2007–2011.  EPSRC. Advancing Machine Learning Methodology for New Classes of Prediction Problems.  (Girolami)
  • 2007-2011.  EPSRC. London Taught Course Centre.
  • 2006-2009.  EPSRC.  Geometrical Methods for Statistical Inference and Decision. (Parry (RF) and Dawid).

(EP/E504485/1)

Page last modified on 14 nov 12 15:24