Numerical Ecology with R
Numerical Ecology with R provides a long-awaited bridge between a textbook in Numerical Ecology and the implementation of this discipline in the R language. After short theoretical overviews, the authors accompany the users through the exploration of the
- PDF / 12,008,373 Bytes
- 315 Pages / 439.37 x 666.142 pts Page_size
- 59 Downloads / 239 Views
se 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 Sarkar: Lattice: Multivariate Data Visualization with R Spector: Data Manipulation with R
Daniel Borcard François Gillet Pierre Legendre ●
Numerical Ecology with R
Daniel Borcard Département de sciences biologiques Université de Montréal C.P. 6128, succursale Centre-ville Montréal, Québec H3C 3J7 Canada [email protected]
Pierre Legendre Département de sciences biologiques Université de Montréal C.P. 6128, succursale Centre-ville Montréal, Québec H3C 3J7 Canada [email protected]
François Gillet Université de Franche-Comté - CNRS UMR 6249 Chrono-environnement UFR Sciences et Techniques 16, Route de Gray F-25030 Besançon cedex France [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 G. Parmigiani The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University 550 North Broadway Baltimore, MD 2105-2011 USA
ISBN 978-1-4419-7975-9 e-ISBN 978-1-4419-7976-6 DOI 10.1007/978-1-4419-7976-6 Springer New York Dordrecht London Heidelberg © Springer Science+Business Media, LLC 2011 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
Ecology is sexy. Teaching ecology is therefore the art of presenting a fascinating topic to well-predisposed audiences. It is not easy: the complexities of modern ecological science go well beyond the introductory chapters taught in high schools or the marvellous movies about ecosystems presented on TV. But well-predisposed audiences are ready to make the effort. Numerical ecology is another story. For some unclear reasons, a majority of ecology-oriented people are strangely reluctant when it comes to quantifying nature and us
Data Loading...
