Stochastic Inverse Regression and Reproducing Kernel Hilbert Space : with Applications in Functional Data Analysis

Language: English

Published by VDM Verlag Dr. Müller, 2009

3639177924 / 9783639177923

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - The basic philosophy of Functional Data Analysis (FDA) is to think of the observed data functions as elements of a possibly infinite-dimensional function space. Most of the current research topics on FDA focus on advancing theoretical tools and extending existing multivariate techniques to accommodate the infinite-dimensional nature of data. This monograph reports contributions on both fronts, where a unifying inverse regression theory for both themultivariate setting and functional data from a Reproducing Kernel Hilbert Space (RKHS) prospective is developed. We proposed a stochastic multiple-index model, two RKHS-related inverse regression procedures, a ``slicing'' approach and a kernel approach, as well as an asymptotic theory were introduced to the statistical framework. Some general computational issues of FDA were discussed, Somegeneral computational issues of FDA were discussed, which led to smoothed versions of the stochastic inverse regression methods.…

Seller Inventory # 9783639177923

Title
Stochastic Inverse Regression and Reproducing Kernel Hilbert Space : with Applications in Functional Data Analysis
Author
Haobo Ren
Publisher
VDM Verlag Dr. Müller
Publication year
2009
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3639177924
ISBN 13
9783639177923
Item weight
160 grams
Dimensions
220x150x7 mm

AHA-BUCH GmbH

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