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Functional Data Analysis

Functional Data Analysis

Functional Data Analysis
Stock photo: cover may vary

Functional Data Analysis Hardback - 1997

by Ramsay, J. O

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  • Hardback

Description

Springer, 1997. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,700grams, ISBN:9780387949567
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Details

  • Title Functional Data Analysis
  • Author Ramsay, J. O
  • Binding Hardback
  • Edition First printing
  • Pages 310
  • Volumes 1
  • Language ENG
  • Publisher Springer, New York
  • Publication date 1997
  • Illustrated Yes
  • Bookseller's Inventory # 9978260
  • ISBN 9780387949567 / 0387949569
  • Weight 1.34 lbs (0.61 kg)
  • Dimensions 9.68 x 6.3 x 0.81 in (24.59 x 16.00 x 2.06 cm)
  • Category Mathematics
  • Library of Congress subjects Multivariate analysis
  • Library of Congress Catalogue Number 96054729
  • Dewey Decimal Code 519.5

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Reader reviews for Functional Data Analysis

From the publisher

Scientists today collect samples of curves and other functional observations. This monograph presents many ideas and techniques for such data. Included are expressions in the functional domain of such classics as linear regression, principal components analysis, linear modelling, and canonical correlation analysis, as well as specifically functional techniques such as curve registration and principal differential analysis. Data arising in real applications are used throughout for both motivation and illustration, showing how functional approaches allow us to see new things, especially by exploiting the smoothness of the processes generating the data. The data sets exemplify the wide scope of functional data analysis; they are drawn from growth analysis, meterology, biomechanics, equine science, economics, and medicine. The book presents novel statistical technology while keeping the mathematical level widely accessible. It is designed to appeal to students, to applied data analysts, and to experienced researchers; it will have value both within statistics and across a broad spectrum of other fields. Much of the material is based on the authors' own work, some of which appears here
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