Functional Data Analysis with R and MATLAB
Scientists often collect samples of curves and other functional observations, and develop models where parameters are also functions. This volume in the UseR! Series is aimed at a wide range of readers, and especially those who would like apply these tech
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J.O. Ramsay Giles Hooker Spencer Graves
Functional Data Analysis with R and MATLAB
J.O. Ramsay 2748, Howe Street Ottawa, ON K2B 6W9 Canada [email protected]
Giles Hooker Department of Biological Statistics & Computational Biology Cornell University 1186, Comstock Hall Ithaca, NY 14853 USA [email protected]
Spencer Graves Productive Systems Engineering 751, Emerson Ct. San Jose, CA 95126 USA [email protected]
Series Editors: Robert Gentleman Program in Computational Biology Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100, Fairview Avenue, N. M2-B876 Seattle, Washington 98109 USA
Kurt Hornik Department of Statistik and Mathematik Wirtschaftsuniversität Wien Augasse 2-6 A-1090 Wien Austria
Giovanni Parmigiani The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University 550, North Broadway Baltimore, MD 21205-2011 USA
ISBN 978-0-387-98184-0 e-ISBN 978-0-387-98185-7 DOI 10.1007/978-0-387-98185-7 Springer Dordrecht Heidelberg London New York Library of Congress Control Number: 2009928040 © Springer Science+Business Media, LLC 2009 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights.
Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
This contribution to the useR! series by Springer is designed to show newcomers how to do functional data analysis in the two popular languages, Matlab and R. We hope that this book will substantially reduce the time and effort required to use these techniques to gain valuable insights in a wide variety of applications. We also hope that the practical examples in this book will make this learning process fun, interesting and memorable. We have tried to choose rich, real-world problems where the optimal analysis has yet to be performed. We have found that applying a spectrum of methods provides more insight than any single approach by itself. Experimenting with graphics and other displays of results is essential. To support the acquisition of expertise, the “scripts” subdirectory of the companion fda package for R includes files with names like “fdarm-ch01.R”, which contain commands in R to reproduce virtually all of the examples (and figures) in the book. This can be found on any computer with R and fda installed
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