Computational Statistics

Theme Overview

This theme is concerned with advancing the theory, methodology, algorithmic development and application of simulation based approaches, such as Markov Chain Monte Carlo, to statistical inference.

Theme Members

Name Keywords
Ricardo Silva   (Theme Lead)
Alexandros Beskos  
Maria De Iorio
Tom Fearn Bayesian methods, calibration, classification, multivariate analysis, near infrared spectroscopy
Serge Guillas  
Christian Henning biogeography, cluster analysis, multivariate data analysis, musicology, robust methods
Ioannis Kosmidis  
Jinghao Xue   

Current and Recent Externally Funded Projects

  • Sequential Monte Carlo methods for applications in high dimensions - EPSRC EP/J01365X/1 - 2012 to 2013 (PI: Beskos)
  • Learning Highly Structured Sparse Latent Variable Models - EPSRC EP/J013293/1 - 2012 to 2013 (PI: Silva)

Page last modified on 17 feb 15 16:46