Gaussian Process Regression Analysis for Functional Data PDF
By:Jian Qing Shi,Taeryon Choi
Published on 2011-07-01 by CRC Press
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 dimensional data and variable selection. The remainder of the text explores advanced topics of functional regression analysis, including novel nonparametric statistical methods for curve prediction, curve clustering, functional ANOVA, and functional regression analysis of batch data, repeated curves, and non-Gaussian data. Many flexible models based on Gaussian processes provide efficient ways of model learning, interpreting model structure, and carrying out inference, particularly when dealing with large dimensional functional data. This book shows how to use these Gaussian process regression models in the analysis of functional data. Some MATLAB® and C codes are available on the first author’s website.
This Book was ranked at 33 by Google Books for keyword Science Math Biological Sciences novel.
Book ID of Gaussian Process Regression Analysis for Functional Data's Books is DkgdN6dRAicC, Book which was written byJian Qing Shi,Taeryon Choihave ETAG "WqO6vMU+5c8"
Book which was published by CRC Press since 2011-07-01 have ISBNs, ISBN 13 Code is 9781439837733 and ISBN 10 Code is 1439837732
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