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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:
Acceso en línea:http://cds.cern.ch/record/1985585
Descripción
Sumario: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