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Thesis

Highly comparative time-series analysis

Abstract:

In this thesis, a highly comparative framework for time-series analysis is developed. The approach draws on large, interdisciplinary collections of over 9000 time-series analysis methods, or operations, and over 30 000 time series, which we have assembled. Statistical learning methods were used to analyze structure in the set of operations applied to the time series, allowing us to relate different types of scientific methods to one another, and to investigate redundancy across them. An an...

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Institution:
University of Oxford
Oxford college:
Balliol College
Department:
Mathematical,Physical & Life Sciences Division - Physics
Role:
Author

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Role:
Supervisor
Role:
Supervisor
Publication date:
2012
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
Oxford University, UK
URN:
uuid:642b65cf-4686-4709-9f9d-135e73cfe12e
Local pid:
ora:7587

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