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Numerische Ökologie mit R von François Gillet, Daniel Borcard und Pierre Legendre-
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- Sofort-KaufenNumerische Ökologie mit R von François Gillet, Daniel Borcard und Pierre Legendre
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eBay-Artikelnr.:177426999245
Artikelmerkmale
- Artikelzustand
- ISBN
- 9783319714035
Über dieses Produkt
Product Identifiers
Publisher
Springer International Publishing A&G
ISBN-10
3319714031
ISBN-13
9783319714035
eBay Product ID (ePID)
240096295
Product Key Features
Number of Pages
Xv, 435 Pages
Publication Name
Numerical Ecology with R
Language
English
Publication Year
2018
Subject
Life Sciences / Ecology, Programming Languages / General, Environmental Science (See Also Chemistry / Environmental), Probability & Statistics / General
Type
Textbook
Subject Area
Mathematics, Computers, Science
Series
Use R! Ser.
Format
Trade Paperback
Dimensions
Item Weight
239.4 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Edition Number
2
Dewey Edition
22
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
577.02855133
Table Of Content
Chapter 1. Introduction.- Chapter 2. Exploratory Data Analysis.- Chapter 3. Association Measures and Matrices.- Chapter 4. Cluster Analysis.- Chapter 5. Unconstrained Ordination.- Chapter 6. Canonical Ordination.- Chapter 7. Spatial Analysis of Ecological Data.- Chapter 8. Community Diversity.
Synopsis
Offers an up-to-date, practical guide to numerical ecology from leaders in the field Provides complete data sets, functions and scripts Includes examples with extensive commentaries, 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 methods by means of applied and extensively commented examples. Users are invited to use this book as a teaching companion at the computer. The travel starts with exploratory approaches, proceeds with the construction of association matrices, then addresses three families of methods: clustering, unconstrained and canonical ordination, and spatial analysis. All the necessary data files, the scripts used in the chapters, as well as the extra R functions and packages written by the authors, can be downloaded from a web page accessible through the Springer web site (http://www.bio.umontreal.ca/numecolR/). This book is aimed at professional researchers, practitioners, graduate students and teachers in ecology, environmental science and engineering, and in related fields such as oceanography, molecular ecology, agriculture and soil science, who already have a background in general and multivariate statistics and wish to apply this knowledge to their data using the R language, as well as people willing to accompany their disciplinary learning with practical applications. People from other fields (e.g. geology, geography, paleoecology, phylogenetics, anthropology, the social and education sciences, etc.) may also benefit from the materials presented in this book. The three authors teach numerical ecology, both theoretical and practical, to a wide array of audiences, in regular courses in their Universities and in short courses given around the world. Daniel Borcard is lecturer of Biostatistics and Ecology and researcher in Numerical Ecology at Université de Montréal, Québec, Canada. François Gillet is professor of Community Ecology and Ecological Modelling at Université de Franche-Comté, Besançon, France. Pierre Legendre is professor of Quantitative Biology and Ecology at Université de Montréal, Fellow of the Royal Society of Canada, and ISI Highly Cited Researcher in Ecology/Environment., 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 methods by means of applied and extensively commented examples. Users are invited to use this book as a teaching companion at the computer. The travel starts with exploratory approaches, proceeds with the construction of association matrices, then addresses three families of methods: clustering, unconstrained and canonical ordination, and spatial analysis. All the necessary data files, the scripts used in the chapters, as well as the extra R functions and packages written by the authors, can be downloaded from a web page accessible through the Springer web site (http: //www.bio.umontreal.ca/numecolR/). This book is aimed at professional researchers, practitioners, graduate students and teachers in ecology, environmental science and engineering, and in related fields such as oceanography, molecular ecology, agriculture and soil science, who already have a background in general and multivariate statistics and wish to apply this knowledge to their data using the R language, as well as people willing to accompany their disciplinary learning with practical applications. People from other fields (e.g. geology, geography, paleoecology, phylogenetics, anthropology, the social and education sciences, etc.) may also benefit from the materials presented in this book. The three authors teach numerical ecology, both theoretical and practical, to a wide array of audiences, in regular courses in their Universities and in short courses given around the world. Daniel Borcard is lecturer of Biostatistics and Ecology and researcher in Numerical Ecology at Universit de Montr al, Qu bec, Canada. Fran ois Gillet is professor of Community Ecology and Ecological Modelling at Universit de Franche-Comt , Besan on, France. Pierre Legendre is professor of Quantitative Biology and Ecology at Universit de Montr al, Fellow of the Royal Society of Canada, and ISI Highly Cited Researcher in Ecology/Environment., This new edition of Numerical Ecology with R guides readers through an applied exploration of the major methods of multivariate data analysis, as seen through the eyes of three ecologists. It provides a bridge between a textbook of numerical ecology and the implementation of this discipline in the R language. The book begins by examining some exploratory approaches. It proceeds logically with the construction of the key building blocks of most methods, i.e. association measures and matrices, and then submits example data to three families of approaches: clustering, ordination and canonical ordination. The last two chapters make use of these methods to explore important and contemporary issues in ecology: the analysis of spatial structures and of community diversity. The aims of methods thus range from descriptive to explanatory and predictive and encompass a wide variety of approaches that should provide readers with an extensive toolbox that can address a wide palette of questions arising in contemporary multivariate ecological analysis. The second edition of this book features a complete revision to the R code and offers improved procedures and more diverse applications of the major methods. It also highlights important changes in the methods and expands upon topics such as multiple correspondence analysis, principal response curves and co-correspondence analysis. New features include the study of relationships between species traits and the environment, and community diversity analysis. This book is aimed at professional researchers, practitioners, graduate students and teachers in ecology, environmental science and engineering, and in related fields such as oceanography, molecular ecology, agriculture and soil science, who already have a background in general and multivariate statistics and wish to apply this knowledge to their data using the R language, as well as people willing to accompany their disciplinary learning with practical applications. People from other fields (e.g. geology, geography, paleoecology, phylogenetics, anthropology, the social and education sciences, etc.) may also benefit from the materials presented in this book. Users are invited to use this book as a teaching companion at the computer. All the necessary data files, the scripts used in the chapters, as well as extra R functions and packages written by the authors of the book, are available online (URL: http://adn.biol.umontreal.ca/~numericalecology/numecolR/)., This much anticipated volume maps the connections between numerical ecology and its implementation in the 'R' language. Beginning with concise theoretical overviews, the authors go on to explore the methodology using applied and extensively annotated examples.
LC Classification Number
QA276-280
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- g***1 (387)- Bewertung vom Käufer.Letzte 6 MonateBestätigter KaufSo excited to get this book and CD. Great seller A+++ fast delivery very happy and great condition. Thank you for wrapping book so it didn't get damaged in anyway. Great value and exactly how described - very happy. Thank you :)
- s***s (1031)- Bewertung vom Käufer.Letzter MonatBestätigter KaufI ordered this book on 9/27/2025, a Saturday, the seller is so thoughtful that they got the book ready for shipping and then took it to the post office all before 11:00AM. Other sellers should strive to be like this seller.Antwort von tomboleware- Verkäufer tomboleware hat auf Bewertung reagiert.- Verkäufer tomboleware hat auf Bewertung reagiert.Thank you for the purchase, and I really appreciate the kind words.