| EPSRC Reference: |
GR/T29253/01 |
| Title: |
Nonparametric Methods for Curve Fitting and Prediction with Large Data-sets |
| Principal Investigator: |
Shi, Dr JQ |
| Other Investigators: |
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| Project Partners: |
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| Department: |
Mathematics and Statistics |
| Organisation: |
Newcastle University |
| Scheme: |
First Grant Scheme Pre-FEC |
| Starts: |
01 March 2005 |
Ends: |
31 August 2007 |
Value (£): |
121,691
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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 overall aim of this project is to develop statistical methodology and the statistical theory for curve fitting and related problems, focusing particular on the problems with large data-sets and with large dimensional input covariates, and to apply them to the modelling and control of nonlinear dynamic systems in engineering. We will extend the idea of mixtures and Gaussian processes to cover a much wider class of models and data structures; to explore ways of modelling the mean and covariance structures by combining local parametric and non-parametric approaches; and to develop efficient algorithms suitable for automatic machine learning and further applications. The core statistical techniques used in this project to analyse the data in rehabilitation engineering will enable new insight into the related engineering problems.
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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.ncl.ac.uk |