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Details of Grant 

EPSRC Reference: GR/S80615/01
Title: Modern statistical approaches to increment/decrement models: an investigation in Bayesian regression for multiple state Markov models
Principal Investigator: Holmes, Professor C
Other Investigators:
Hand, Professor D
Researcher Co-Investigators:
Project Partners:
Department: Statistics
Organisation: University of Oxford
Scheme: Standard Research (Pre-FEC)
Starts: 20 September 2004 Ends: 19 September 2006 Value (£): 109,497
EPSRC Research Topic Classifications:
Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
Financial Services
Related Grants:
Panel History:  
Summary on Grant Application Form
Our objective is to investigate novel statistical methods for modelling mortality data and financial event history data, such as the status of customer loan repayment.In this respect we propose to investigate nonlinear stochastic (Bayesian) regression functions for modelling state transition rates within multiple state Markov models (MSMMs). These models can be used to track the dynamic behavior of individuals as they switch between states, where the states refer to conditions such as alive , dead or defaulted on loan , repaid etc.Our Bayesian methodology will investigate nonlinear approaches to modelling the probability of an individual switching status as a function of time. Moreover, we will seek to incorporate other information, such as age, sex etc into the switching probability functions.The methodology necessitates numerical integration to calculate the probability of the models. This will require research in Markov chain Monte Carlo simulation.
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Organisation Website: http://www.ox.ac.uk