| EPSRC Reference: |
EP/P031447/1 |
| Title: |
Statistical methodology and theory for the Big Data era (Ext.) |
| Principal Investigator: |
Samworth, Professor RJ |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Pure Maths and Mathematical Statistics |
| Organisation: |
University of Cambridge |
| Scheme: |
EPSRC Fellowship |
| Starts: |
01 December 2017 |
Ends: |
31 August 2021 |
Value (£): |
610,894
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| EPSRC Research Topic Classifications: |
| Statistics & Appl. Probability |
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| EPSRC Industrial Sector Classifications: |
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Summary on Grant Application Form |
This is an extension of the Fellowship 'New challenges in
high-dimensional statistical inference' (EP/J017213/1).
The project will involve developing methodology and theory for a range
of modern statistical problems from high-dimensional and nonparametric
statistical inference. Such problems lie at the heart of modern
data science, an area where the UK urgently needs to grow its capacity.
Specific challenges to be addressed include the development of methods
for dimension reduction, variable selection and uncertainty
quantification, among several others. These are some of the
fundamental problems faced by practitioners in the Big Data era, and
demand highly innovative solutions. Our proposed techniques will be
proven to be robust via appropriate theoretical justification, and
will be implemented in free, open source software so as to maximise
the impact of the 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 |