| EPSRC Reference: |
GR/A00537/01 |
| Title: |
BAYESIAN MODELLING OF COMPLEX STOCHASTIC SYSTEMS |
| Principal Investigator: |
Brooks, Professor SP |
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| Department: |
Pure Maths and Mathematical Statistics |
| Organisation: |
University of Cambridge |
| Scheme: |
Advanced Fellowship (Pre-FEC) |
| Starts: |
01 August 2000 |
Ends: |
31 July 2005 |
Value (£): |
203,775
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| EPSRC Research Topic Classifications: |
| Statistics & Appl. Probability |
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| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
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Summary on Grant Application Form |
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The general aim of this ambitious research programme is to develop novel methodology in the field of Markov chain Monte Carlo (MCMC), a simulation method for exploring high dimensional probability surfaces. These surfaces are of interest as they can be used to represent our beliefs about the properties and behaviour of a stochastic system. In order to make inference about the system, we require a mechanism for exploring and summarising these complex surfaces. MCMC methods provide such a mechanism and are already widely applied in many areas of science.The proposed research will be strongly directed by collaboration with fellow scientists and engineers. In particular, appropriate methodology will be developed to study accurate and reliable stochastic models for radiocarbon dating, for crack detection in electrically conducting media, for measuring and predicting the environmental impact of changes in farming practices and for studying wildlife populations, amongst others.Each of these areas poses distinct and challenging problems but can be tackled within the same general framework, using MCMC methods. This project aims to formalise this framework, to develop methodology for tackling the specific questions posed by collaborators, to apply this new methodology and to raise the profile of these powerful new techniques so that scientists and engineers from a wide range of disciplines are aware of the impact that these methods might have on their own research.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.cam.ac.uk |