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Theoretical foundations of functional data analysis, with an introduction to linear operators
Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators provides a uniquely broad compendium of the key mathematical concepts and results that are relevant for the theoretical development of functional data analysis (FDA).The self-contained treatment of selected...
Autores principales: | , |
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Lenguaje: | eng |
Publicado: |
Wiley
2015
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Acceso en línea: | http://cds.cern.ch/record/2020223 |
_version_ | 1780946836615331840 |
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author | Hsing, Tailen Eubank, Randall |
author_facet | Hsing, Tailen Eubank, Randall |
author_sort | Hsing, Tailen |
collection | CERN |
description | Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators provides a uniquely broad compendium of the key mathematical concepts and results that are relevant for the theoretical development of functional data analysis (FDA).The self-contained treatment of selected topics of functional analysis and operator theory includes reproducing kernel Hilbert spaces, singular value decomposition of compact operators on Hilbert spaces and perturbation theory for both self-adjoint and non self-adjoint operators. The probabilistic foundation for FDA is described from the |
id | cern-2020223 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2015 |
publisher | Wiley |
record_format | invenio |
spelling | cern-20202232021-04-21T20:17:34Zhttp://cds.cern.ch/record/2020223engHsing, TailenEubank, RandallTheoretical foundations of functional data analysis, with an introduction to linear operatorsMathematical Physics and MathematicsTheoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators provides a uniquely broad compendium of the key mathematical concepts and results that are relevant for the theoretical development of functional data analysis (FDA).The self-contained treatment of selected topics of functional analysis and operator theory includes reproducing kernel Hilbert spaces, singular value decomposition of compact operators on Hilbert spaces and perturbation theory for both self-adjoint and non self-adjoint operators. The probabilistic foundation for FDA is described from theWileyoai:cds.cern.ch:20202232015 |
spellingShingle | Mathematical Physics and Mathematics Hsing, Tailen Eubank, Randall Theoretical foundations of functional data analysis, with an introduction to linear operators |
title | Theoretical foundations of functional data analysis, with an introduction to linear operators |
title_full | Theoretical foundations of functional data analysis, with an introduction to linear operators |
title_fullStr | Theoretical foundations of functional data analysis, with an introduction to linear operators |
title_full_unstemmed | Theoretical foundations of functional data analysis, with an introduction to linear operators |
title_short | Theoretical foundations of functional data analysis, with an introduction to linear operators |
title_sort | theoretical foundations of functional data analysis, with an introduction to linear operators |
topic | Mathematical Physics and Mathematics |
url | http://cds.cern.ch/record/2020223 |
work_keys_str_mv | AT hsingtailen theoreticalfoundationsoffunctionaldataanalysiswithanintroductiontolinearoperators AT eubankrandall theoreticalfoundationsoffunctionaldataanalysiswithanintroductiontolinearoperators |