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Stochastic Modelling and Time Series


Theme Overview

The research carried out under this theme covers the development of generic stochastic models and the investigation of their properties, as well as modelling and inference for applications in a range of physical and biological sciences. Major components include:

  • modeling and inference for spatial-temporal processes, with important applications in environmental sciences including hydrology, climatology, and atmospheric science;
  • modeling and inference for complex computer models (e.g. climate and tsunami models);
  • theoretical research on epidemic models and genetics, leading to applications in the life sciences and insight on biological mechanisms;

Theme members

Name Keywords
Serge Guillas (Theme Lead) Emulation and calibration of computer models; functional data analysis; time series; tsunami modeling
Richard Chandler
Climatology; hydrology; inference for stochastic models; multimodel ensembles; space-time modelling; statistical downscaling; trend analysis; uncertainty analysis
Petros Dellaportas
Hidden Markov models; volatility time series models
Simon Harden
Spatial point processes
Valerie Isham
Applied probability; epidemics; hydrology; models for random networks;  point processes; population processes; spatial and spatio-temporal processes
Giampiero Marra
Energy economics; spatio-temporal modelling
James Nelson
Harmonic analysis; multiresolution analysis; random fields; regularisation
Paul Northrop
Climatology; hydrology; inference for stochastic models; modelling of extreme values; multimodel ensembles; offshore engineering; rainfall modelling 
Sofia Olhede
Ecology; earth science; neuroscience; oceanography
Gareth Peters Hidden Markov models; spatial point processes; state space models
Matina Rassias
Stochastic functional differential equations and applications
Gordon Ross
Bayesian methods; change points; nonparametric statistics; nonstationary processes; point processes
Afzal Siddiqui
Energy economics; risk management
Hilde Wilkinson-Herbots
Applications of probability and stochastic processes to problems in genetics; epidemic models

Other members: Alexandros BeskosFranz KirályPatrick Wolfe.

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

Current and Recent Externally Funded Projects

  • Knowledge Transfer Partnership: Combination of earthquake and tsunami catastrophe models, £173k, EPSRC & NERC (50%) and Aspen Insurance Ltd (50%), Nov 2014 - Oct 2016, PI: Guillas.
  • A demonstration tsunami catastrophe risk model for the insurance industry, £97k, NERC NE/L002752/1, Oct 2013 - Jun 2014, PI: Guillas.
  • Probability, Uncertainty and Risk in the Natural Environment, £683k, NERC NE/J017434/1, Aug 2012 - Aug 2016, PI: Chandler.
  • An Options Approach to UK Energy Futures, £130k, NERC NE/GOO7748/1, Oct 2011 – Jun 2012, CI: Siddiqui.
  • Hydrological extremes and feedbacks in the changing water cycle, £184k, NERC NE/I006656/1, Feb 2011 - Feb 2014, PI: Chandler.
  • Stratospheric ozone and climate change, £44k, Leverhulme Trust, Jan 2011 - Dec 2012, PI: Guillas.
  • 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.

Page last modified on 10 mar 15 14:43