| EPSRC Reference: |
GR/M94120/01 |
| Title: |
MODELLING SHORT MULTIVARIATE TIME SERIES |
| Principal Investigator: |
Liu, Professor X |
| Other Investigators: |
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| Department: |
Computer Science and Information Systems |
| Organisation: |
Birkbeck College |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 April 2000 |
Ends: |
01 October 2000 |
Value (£): |
38,774
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Information & Knowledge Mgmt |
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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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Many sttistical Multivariate Time Series (MTS) modelling methods place constraints on the minimum number of observations in the dataset, and require distribution assumptions to be made regarding the observed time series, eg the maximum likelihood method for parameter estimation. To date, we have developed a fast and approxiamte method based on evolutionary programming techniques to locate variables that are highly correlated within high-dimensional MTS. We have also demonstrated the promises of automated model order selection and parameter estimation using genetic algorithms. Specifically the method bypassed the size restrictions of the statistical mehtods, made no distribution assumptions, and also located the order and associated parameters as a whole step. The proposed research will extend the current work on modelling MTS data into a coherent methodology for forecasting purposes. This will be achieved by developing methods for model selection based on the current variable selection work, by improving the existing mehtods for model order selection and parameter estimation, and by integrating the above into an effective forecasting methodology. This methodology will be tested on medical and process data.
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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.bbk.ac.uk/ |