Gaussian process regression analysis for functional data

Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed co...

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Detalles Bibliográficos
Autores principales: Shi, Jian Qing, Choi, Taeryon
Lenguaje:eng
Publicado: Taylor and Francis 2011
Materias:
Mathematical Physics and Mathematics
Acceso en línea:http://cds.cern.ch/record/1985585
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author Shi, Jian Qing
Choi, Taeryon
author_facet Shi, Jian Qing
Choi, Taeryon
author_sort Shi, Jian Qing
collection CERN
description Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed covariates of functional and scalar variables.Covering the basics of Gaussian process regression, the first several chapters discuss functional data analysis, theoretical aspects based on the asymptotic properties of Gaussian process regression models, and new methodological developments for high dime
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2011
publisher Taylor and Francis
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spelling cern-19855852021-04-21T20:37:19Zhttp://cds.cern.ch/record/1985585engShi, Jian QingChoi, TaeryonGaussian process regression analysis for functional dataMathematical Physics and MathematicsGaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed covariates of functional and scalar variables.Covering the basics of Gaussian process regression, the first several chapters discuss functional data analysis, theoretical aspects based on the asymptotic properties of Gaussian process regression models, and new methodological developments for high dimeTaylor and Francisoai:cds.cern.ch:19855852011
spellingShingle Mathematical Physics and Mathematics
Shi, Jian Qing
Choi, Taeryon
Gaussian process regression analysis for functional data
title Gaussian process regression analysis for functional data
title_full Gaussian process regression analysis for functional data
title_fullStr Gaussian process regression analysis for functional data
title_full_unstemmed Gaussian process regression analysis for functional data
title_short Gaussian process regression analysis for functional data
title_sort gaussian process regression analysis for functional data
topic Mathematical Physics and Mathematics
url http://cds.cern.ch/record/1985585
work_keys_str_mv AT shijianqing gaussianprocessregressionanalysisforfunctionaldata
AT choitaeryon gaussianprocessregressionanalysisforfunctionaldata

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