| EPSRC Reference: |
GR/L55650/01 |
| Title: |
ADAPTIVE MARKOV CHAIN MONTE CARLO METHODS FOR STATISTICAL MODELLING |
| Principal Investigator: |
Brooks, Professor SP |
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| Department: |
Mathematics |
| Organisation: |
University of Bristol |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 October 1997 |
Ends: |
30 September 2000 |
Value (£): |
53,216
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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 project is to develop novel methodology in the field of Markov Chain Monte Carlo (MCMC), a simulative method for exploring high dimensional probability surfaces, and widely applied to many statistical modelling problems.Bayesian statistics allows us to represent our beliefs about a stochastic system in terms of an often high dimensional probability surface. 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 widely applied in all areas of science where stochastic systems are of interest.The aim of the project is to produce an efficient and intelligent mechanism for exploring these surfaces and which effectively learns about the surface in order to modify its future behaviour. Such methods will provide usable statistical tools that are able to optimise their performance and which require little specialist knowledge to apply them effectively. These methods could be applied to the full range of statistical applications in the field of science and engineering. Particular emphasis will be placed on mechanisms for adaptive learning and on the implementational aspects of the methods.
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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.bris.ac.uk |