Projects and Assignments List in Statistics for year 2013-2014

Alexander Veretennikov (ext.: 35183, email:, office: 8.22c)

You may also consult the old link at

The list of topics is tentative; variations are possible and in some cases your own topic may be approved. Some of the topics from the list may be taken by more than one student. In some cases a topic may be supervised by another staff member.

The links to Pure and Applied coordinators: Prof Paul P. Martin

and Dr Oleg Chalykh and


  • Project Handbook here (this is a 2011/12 version) and here (2012/2013, the changes are minimal)
  • Project student/supervisor agreement form HERE.
  • Unless specified otherwise, each topic may be suitable for 3rd and 4th year project/assignment.

All topics available in 2012/2013 remain available in 2013/2014



  • Statistical methods for spatial data (Level 3 or Level 4) R.G.Aykroyd
  • Using random walks in exchange rate modelling (Level 3 or Level 4)    R.G.Aykroyd
  • Exact independence testing in contingency tables using MCMC methods (Level 4)  R.G.Aykroyd
  • Statistical modelling of epidemics                                 A.J.Baczkowski
  • Time series (spectral methods)                                       A.J.Baczkowski
  • Statistical clustering methods                                        A.J.Baczkowski
  • Computer simulation methods                                       A.J.Baczkowski
  • Testing randomness of a sequence of digits                  A.J.Baczkowski
  • Circular data                                                                   A.J.Baczkowski
  • Modelling species abundance                                         A.J.Baczkowski
  • Bootstrapping   (NOT offered at the 5th level)               S.Barber
  • Sequential clinical trials                                                   S.Barber
  • Wavelet methods in statistics                                          S.Barber
  • Minority Game as an adaptive model of interacting agents in financial markets    L.V.Bogachev
  • Extreme Value Theory: limit laws and Pareto distribution       L.V.Bogachev
  • Random Walks in Random Environments                                L.V.Bogachev
  • Random partitions and their limit shape                                   L.V.Bogachev
  • Random Matrix Theory: basics and spectral asymptotics         L.V.Bogachev
  • Exploring contact protein matrices                                                       W.Gilks (available only in semester 2)
  • Predicting the 3D structure of genomes using DNA contact matrices W.Gilks (available only in semester 2)
  • Predicting specificity determining sites in protein sequence alignments W.Gilks (available only in semester 2)
  • A data analysis on the American 2000 Election (3 level) C.C.Taylor
  • Quantitative decision analysis in sports betting (levels 3-4) J.P.Gosling
  • Gaussian process emulation of complex computer models (levels 3-4) J.P.Gosling
  • Partial Least Squares Regression                                      A.Gusnanto
  • Multiple testing and false discovery rate in microarray data analysis A.Gusnanto
  • Shape analysis (3-4 level)                                                 J.T.Kent
  • The EM algorithm (3-4 level)                                           J.T.Kent
  • Benford’s law (3 level)                                                    J.T.Kent
  • Nonparametric density estimation                                   C.C.Taylor
  • Statistical analysis of point patterns                                C.C.Taylor
  • Statistical pattern recognition                                          C.C.Taylor
  • Representing & analysing statistical problems using Bayesian Networks                 P.Thwaites
  • Investigating the effects of causal manipulation of variables within a statistical model  P.Thwaites
  • Extreme values theory  (3-4 level)                                      A.Yu.Veretennikov
  • Prediction of random sequences and tracking a signal under a random noise (3-4 level) A.Yu.Veretennikov
  • Rate of convergence to equilibrium for Markov chain with applications to Markov Chain Monte Carlo (3-4 level) A.Yu.Veretennikov
  • Markov chains as discretization methods for solving partial differential equations (3-4 level) A.Yu.Veretennikov
  • Linear algebra methods for analysing ergodicity of Markov chains (3-4 level) A.Yu.Veretennikov
  • Probabilistic techniques in Analysis and Complex Analysis (3-4 level) A.Yu.Veretennikov
  • Multilevel Monte Carlo path simulations (3-4 level)  J.Voss (see also )
  • Random number generation (3-4 level)                      J.Voss
  • Introduction to the theory of large deviations (3-4 level)  J.Voss, A.Yu.Veretennikov (notice that the abstracts and literature are different, although the title is the same)
  • Numerical simulations of stochastic differential equations J.Voss
  • Approximate Bayesian Computation                                      J.Voss
  • Estimating the Intensity Function of a Poisson Process  (4 level)  J.Voss


This page is maintained by A.Yu.Veretennikov and was last updated on 17 June 2012