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Applied Functional Data Analysis: Methods and Case Studies de J.O. Ramsay

Applied Functional Data Analysis: Methods and Case Studies: Springer Series in Statistics

Autor J.O. Ramsay, B.W. Silverman
en Limba Engleză Paperback – 12 iun 2002
This book contains the ideas of functional data analysis by a number of case studies. The case studies are accessible to research workers in a wide range of disciplines. Every reader should gain not only a specific understanding of the methods of functional data analysis, but more importantly a general insight into the underlying patterns of thought. There is an associated web site with MATLABr and S?PLUSr implementations of the methods discussed.
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Specificații

ISBN-13: 9780387954141
ISBN-10: 0387954147
Pagini: 191
Ilustrații: XII, 191 p.
Dimensiuni: 155 x 235 x 12 mm
Greutate: 0.37 kg
Ediția:2002
Editura: Springer
Colecția Springer
Seria Springer Series in Statistics

Locul publicării:New York, NY, United States

Public țintă

Research

Descriere

Almost as soon as we had completed our previous book Functional Data Analysis in 1997, it became clear that potential interest in the ?eld was far wider than the audience for the thematic presentation we had given there. At the same time, both of us rapidly became involved in relevant new research involving many colleagues in ?elds outside statistics. This book treats the ?eld in a di?erent way, by considering case st- ies arising from our own collaborative research to illustrate how functional data analysis ideas work out in practice in a diverse range of subject areas. These include criminology, economics, archaeology, rheumatology, psych- ogy, neurophysiology, auxology (the study of human growth), meteorology, biomechanics, and education—and also a study of a juggling statistician. Obviously such an approach will not cover the ?eld exhaustively, and in any case functional data analysis is not a hard-edged closed system of thought. Nevertheless we have tried to give a ?avor of the range of meth- ology we ourselves have considered. We hope that our personal experience, including the fun we had working on these projects, will inspire others to extend “functional” thinking to many other statistical contexts. Of course, manyofourcasestudiesrequireddevelopmentofexistingmethodology,and readersshouldgaintheabilitytoadaptmethodstotheirownproblemstoo.

Cuprins

Introduction * Life Course Data in Criminology * The Nondurable Goods Index * Bone Shapes from a Paleopathology Study * Modeling Reaction Time Distributions * Zooming in on Human Growth * Time Warping Handwriting and Weather Records * How do Bone Shapes Indicate Arthritis? * Functional Models for Test Items * Predicting Lip Acceleration from Electromyography * The Dynamics of Handwriting Printed Characters * A Differential Equation for Juggling

Recenzii

From the reviews:
"Analysis of functional data has become a very active area of research in statistics. … Examples discussed in the book are extremely well chosen. They really make the book a very enjoyable reading. This book will surely attract more people into the area of functional data analysis. … the authors have done a commendable job of exposing functional data analysis through a wide variety of examples chosen from diverse fields … . I expect this book to be widely read and referenced in near future." (Probal Chaudhuri, Sankhya, Vol. 63 (4), 2003)
"This book is a follow-up to the monograph Functional Data Analysis (FDA) by the same authors. … This is an unusual book, an interesting book in a field which is still in expansion and where lots of data sets will come up in the future. The data sets and the data analyses are varied and thought-provoking. … the appropriate audience would be graduate students, statistical researchers, and experienced applied statisticians." (Theo Gasser, SIAM Review, Vol. 45 (2), 2003)
"The best-known opportunity for functional data analysis (FDA) is when the data are measurements of a continuous function of time, or some other continuous variable. However, the authors show that the range of application can be much wider. … One of the attractions of this book is the range of examples … . Overall, the book achieves well its main objective of showing what FDA can do. I hope that it succeeds in encouraging the use of powerful data analysis techniques in new application areas." (Tim Auton, Journal of the Royal Statistical Society, Vol. 157 (2), 2004)
"This book deals with functional data analysis from a very applied point of view. … The mentioned case studies are accessible to workers in a wide range of disciplines. … Therefore, the nonmathematically oriented audience will enjoy reading through it … ." (Henri Schurz, Zentralblatt MATH, Vol. 1011, 2003)
"The book complements the same authors’ book on ‘Functional Data Analysis’ … with a number of case studies from a wide range of subject areas. Examples are interestingly and well presented. The analysis methods are rooted in the previous book and are essentially descriptive. Most of them are very closely related to the methods that are widely used in the traditional function approximation theory." (V. V. Fedorov, Short Book Review, Vol. 23 (1), 2003)
"This is one of the most interesting statistics texts I have read! The authors discuss different case studies using data in the form of curves (functions) rather than numbers normally considered by statisticians. … Readers … will find this text informative and easy to understand. … I highly recommend this well-written and reasonably priced text for any statistician or mathematician who uses multivariate analyses and for anyone who may work with functional data. … this text will provide a solid introduction to this field." (Henry W. Altland, Technometrics, Vol. 45 (1), February, 2003)
"The present book introduces and explores the ideas of functional data analysis by the consideration of a number of case studies, many of them presented for the first time. … The case studies are accessible to research workers in a wide range of disciplines. Every reader, whether experienced researcher or graduate student, should gain not only a specific understanding of the methods of functional data analysis, but, more importantly, a general insight into the underlying patterns of thought." (L’Enseignement Mathématique, Vol. 48 (3-4), 2002)

Caracteristici

Includes supplementary material: sn.pub/extras