Dynamic Dependence modelling

Supervisor(s)

Contact Dr Georgios Aivaliotis to discuss this project further informally.

Project description

This project aims at modelling the dependence structure between two time series. Applications include risk management, health, and social science problems. The area is gathering importance due to the recent availability of temporal datasets (for example lifestyle and health status).

This project has several possible directions:

a) Quickest change detection problems, when one is trying to detect as fast as possible a change in the model of dependence as indicated by considering more data. These problems can be addressed by modifying and developing statistical techniques for change point detection as well as filtering.

Or, b) Developing a dynamic model for the correlation or joint trend model. 

Entry requirements

Applications are invited from candidates with or expecting a minimum of a UK upper second class honours degree (2:1), and/or a Master's degree in a relevant degree such as (but not limited to) statistics or mathematics.

If English is not your first language, you must provide evidence that you meet the University's minimum English Language requirements.

How to apply

Formal applications for research degree study should be made online through the university's website. Please state clearly in the research information section that the PhD you wish to be considered for is 'Dynamic Dependence modelling' as well as Dr Georgios Aivaliotis as your proposed supervisor.

We welcome scholarship applications from all suitably-qualified candidates, but UK black and minority ethnic (BME) researchers are currently under-represented in our Postgraduate Research community, and we would therefore particularly encourage applications from UK BME candidates. All scholarships will be awarded on the basis of merit.

If you require any further information please contact the Graduate School Office, e: maps.pgr.admissions@leeds.ac.uk