Function Estimation and Functional Data Analysis

BW Silverman

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

Abstract

The roughness penalty method is widely used in function estimation, and is closely related to methods of regularization well known in numerical analysis. Some background to the development of this method is discussed. The versatility of the method is illustrated by its application to an unusual smoothing problem, involving the estimation of a branching system of curves. The second main focus of the paper is on problems where the data are themselves functions, an area known as functional data analysis. The roughness penalty method is a key component of extensions to the functional context of principal components analysis and canonical correlation analysis. These techniques are described and contrasted, and are illustrated by reference to a set of data on the development of human gait.
Translated title of the contributionFunction estimation and functional data analysis
Original languageEnglish
Title of host publicationFirst European Congress of Mathematics Paris, July 6–10, 1992
Subtitle of host publicationVol. II: Invited Lectures (Part 2)
PublisherBirkhäuser Basel
Pages407-427
Number of pages21
Volume2
ISBN (Electronic)9783034891127
ISBN (Print)9783034899123
DOIs
Publication statusPublished - 1994

Publication series

NameProgress in Mathematics
PublisherSpringer
Volume120
ISSN (Print)0743-1643

Bibliographical note

Publisher: Birkhäuser Verlag, Basel
Other: Eds. A.Joseph, F.Mignot, F.Murat, B.Prum and R.Rentschler

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