Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators



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Éditeur :

Wiley


Collection :

Wiley Series in Probability and Statistics

Paru le : 2015-04-07



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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 perspective of random elements in Hilbert spaces as well as from the viewpoint of continuous time stochastic processes. Nonparametric estimation approaches including kernel and regularized smoothing are also introduced. These tools are then used to investigate the properties of estimators for the mean element, covariance operators, principal components, regression function and canonical correlations. A general treatment of canonical correlations in Hilbert spaces naturally leads to FDA formulations of factor analysis, regression, MANOVA and discriminant analysis.

This book will provide a valuable reference for statisticians and other researchers interested in developing or understanding the mathematical aspects of FDA. It is also suitable for a graduate level special topics course.
Pages
368 pages
Collection
Wiley Series in Probability and Statistics
Parution
2015-04-07
Marque
Wiley
EAN papier
9780470016916
EAN PDF
9781118762561

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
368
Taille du fichier
3482 Ko
Prix
84,35 €
EAN EPUB
9781118762578

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
368
Taille du fichier
51036 Ko
Prix
84,35 €