Nonlinear Regression with R
R is a rapidly evolving lingua franca of graphical display and statistical analysis of experiments from the applied sciences. Currently, R offers a wide range of functionality for nonlinear regression analysis, but the relevant functions, packages and doc
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Use R! Albert: Bayesian Computation with R Bivand/Pebesma/Gómez-Rubio: Applied Spatial Data Analysis with R Cook/Swayne: Interactive and Dynamic Graphics for Data Analysis: With R and GGobi Hahne/Huber/Gentleman/Falcon: Bioconductor Case Studies Paradis: Analysis of Phylogenetics and Evolution with R Pfaff: Analysis of Integrated and Cointegrated Time Series with R Ritz/Streibig: Nonlinear Regression with R Sarkar: Lattice: Multivariate Data Visualization with R Spector: Data Manipulation with R
Christian Ritz • Jens Carl Streibig
Nonlinear Regression with R
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Christian Ritz Department of Basic Sciences and Environment (Statistics) Faculty of Life Sciences University of Copenhagen Thorvaldsensvej 40 DK-1871 Frederiksberg C Denmark [email protected]
Jens Carl Streibig Department of Agriculture and Ecology (Crop Science) Faculty of Life Sciences University of Copenhagen Hoejbakkegaard Allé 13 DK-2630 Taastrup Denmark [email protected]
Series Editors: Robert Gentleman Program in Computational Biology Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N, M2-B876 Seattle, Washington 98109-1024 USA
Kurt Hornik Department für Statistik und 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: 978-0-387-09615-5 DOI: 10.1007/978-0-387-09616-2
e-ISBN: 978-0-387-09616-2
Library of Congress Control Number: 2008938643 c Springer Science+Business Media, LLC 2008 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.com
To Ydun Marie Ritz and in memory of Erik Ritz
Preface
This book is about nonlinear regression analysis with R, in particular, how to use the function nls() and related functions and methods. Range of the book Nonlinear regression may be a confined and narrow topic within statistics. However, the use of nonlinear regression is seen in many applied sciences, ranging from biology to engineering to medicine and pharmacology. Therefore, this book covers a wide range of areas in the examples used. Appendix A lists the disciplines from which data are used in this book. What not to expect This book is not a textbook on nonlinear regression. Basic concepts will be briefly introduced, but the reader in need o
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