UNIVERSITY OF KENT
School of Mathematics, Statistics and Actuarial Science
Statistics Seminar Programme: Autumn Term 2009/2010
The seminars will be held on Thursdays at 2 pm in the Mathematics Lecture
Theatre, located on the ground floor of the Institute of Mathematics, Statistics and
Actuarial Science unless otherwise stated. Tea will be available afterwards. All are
welcome.
October 22
Title
Prof. Simon Godsill (University of Cambridge)
TBA
October 29
Title
Dr. Catriona Queen (Open University)
A graphical dynamic approach to forecasting road traffic flow networks
Abstract: Many roads now have induction loops implanted into the road surface providing
real-time traffic flow data. Traffic flow data are invariably multivariate so that the flows of traffic
upstream and downstream of a particular data collection site S in the network are very
informative about the flows at site S. Despite this, most of the short-term forecasting models
of traffic flows are univariate and consider the flow at site S in isolation. In this paper we use a
Bayesian graphical dynamic model (GDM) for forecasting traffic flow. A GDM is a multivariate
model which uses a graph in which the nodes represent flows at the various data collection
sites, and the links between nodes represent the conditional independence and causal
structure between flows at different sites. The paper will focus on the problem of forecasting
traffic flows in two separate busy motorway networks in the UK.
November 5
Title
Prof. Jennison (University of Bath)
Interim monitoring of clinical trials: decision theory, dynamic programming
and optimal stopping
Abstract:It is standard practice to monitor clinical trials with a view to stopping early if results
are sufficiently positive, or negative, at an interim stage. We shall explain how properties of
stopping boundaries can be calculated and how boundaries can be optimised to minimise
expected sample size while controlling type I and II error probabilities.
Constraints on error probabilities complicate this optimisation problem. However, a solution is
possible via unconstrained Bayes problems which can be solved by dynamic programming.
Optimality can then be expressed as a sample path property, making this an "optimal
stopping" problem in the language of probability theory.
We shall give details of numerical computation and optimisation.
We shall discuss a variety of applications in clinical trial design and also point out connections
with problems arising in financial mathematics.
November 12
Title
Prof. Dankmar Böhning (University of Reading)
Capture-recapture estimation of population size by means of empirical
Bayesian smoothing
November 26
Title
Dr Mounia Hocine (Open University)
The case series method: models and applications
Abstract:The self-controlled case series method can be used to study the temporal
association between a time-varying exposure and an adverse event using data only on cases.
It has been widely used in vaccine safety and pharmacoepidemiology, and has been
extended recently for use in pharmacovigilance. The key advantages are that it has high
efficiency relative to the cohort method and that it is self-controlled: fixed confounders, such
as sex, location, and genetic factors are controlled for implicitly.
Recent models and applications will be presented.
December 3
Title
Prof. Gareth Roberts (University of Warwick)
Bayesian non-parametric analysis of diffusions
December 10
Title
Dr Kostas Kalogeropoulos (London School of Economics)
Diffusion models for physiological processes.
December 17
Title
Prof. Jonathan Forster (University of Southampton)
TBA
Further information is available from Xue Wang, School of Mathematics, Statistics and Actuarial
Science, Cornwallis Building, University of Kent, Canterbury, Kent CT2 7NF (Tel: 01227 823796;
Email: X.Wang@kent.ac.uk) or Web:http://www.kent.ac.uk/ims/seminars/index.html#statistics