Multivariate Analysis of Ecological Data with ade4 [electronic resource] / by Jean Thioulouse, Stéphane Dray, Anne-Béatrice Dufour, Aurélie Siberchicot, Thibaut Jombart, Sandrine Pavoine.

By: Thioulouse, Jean [author.]Contributor(s): Dray, Stéphane | Dufour, Anne-Béatrice | Siberchicot, Aurélie | Jombart, Thibaut | Pavoine, SandrineMaterial type: TextTextPublisher: New York, NY : Springer New York : Imprint: Springer, 2018Edition: 1st ed. 2018Description: XI, 329 p. 166 illus., 113 illus. in color. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781493988501Subject(s): Statistics  | Statistics for Life Sciences, Medicine, Health SciencesDDC classification: 519.5 LOC classification: QA276-280Online resources: Click here to access online
Contents:
Chapter 1: Introduction -- Chapter 2: Useful R functions and data structures -- Chapter 3: The dudi class -- Chapter 4: Multivariate analysis graphs -- Chapter 5: Description of environmental variables structures -- Chapter 6: Description of species structures -- Chapter 7: Taking into account groups of sites -- Chapter 8: Description of species-environment relationships -- Chapter 9: Analysing changes in structures -- Chapter 10: Analysing changes in co-structures -- Chapter 11: Relating species traits to environment -- Chapter 12: Analysing spatial structures -- Chapter 13: Analysing phylogenetic structures -- Chapter 14: Analysing phylogenetic structuresAnalysing patterns of biodiversity.
Summary: This book introduces the ade4 package for R which provides multivariate methods for the analysis of ecological data. It is implemented around the mathematical concept of the duality diagram, and provides a unified framework for multivariate analysis. The authors offer a detailed presentation of the theoretical framework of the duality diagram and also of its application to real-world ecological problems. These two goals may seem contradictory, as they concern two separate groups of scientists, namely statisticians and ecologists. However, statistical ecology has become a scientific discipline of its own, and the good use of multivariate data analysis methods by ecologists implies a fair knowledge of the mathematical properties of these methods. The organization of the book is based on ecological questions, but these questions correspond to particular classes of data analysis methods. The first chapters present both usual and multiway data analysis methods. Further chapters are dedicated for example to the analysis of spatial data, of phylogenetic structures, and of biodiversity patterns. One chapter deals with multivariate data analysis graphs. In each chapter, the basic mathematical definitions of the methods and the outputs of the R functions available in ade4 are detailed in two different boxes. The text of the book itself can be read independently from these boxes. Thus the book offers the opportunity to find information about the ecological situation from which a question raises alongside the mathematical properties of methods that can be applied to answer this question, as well as the details of software outputs. Each example and all the graphs in this book come with executable R code.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
e-Books e-Books Central Library, Sikkim University
519.5 (Browse shelf(Opens below)) Not for loan E-3119
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Chapter 1: Introduction -- Chapter 2: Useful R functions and data structures -- Chapter 3: The dudi class -- Chapter 4: Multivariate analysis graphs -- Chapter 5: Description of environmental variables structures -- Chapter 6: Description of species structures -- Chapter 7: Taking into account groups of sites -- Chapter 8: Description of species-environment relationships -- Chapter 9: Analysing changes in structures -- Chapter 10: Analysing changes in co-structures -- Chapter 11: Relating species traits to environment -- Chapter 12: Analysing spatial structures -- Chapter 13: Analysing phylogenetic structures -- Chapter 14: Analysing phylogenetic structuresAnalysing patterns of biodiversity.

This book introduces the ade4 package for R which provides multivariate methods for the analysis of ecological data. It is implemented around the mathematical concept of the duality diagram, and provides a unified framework for multivariate analysis. The authors offer a detailed presentation of the theoretical framework of the duality diagram and also of its application to real-world ecological problems. These two goals may seem contradictory, as they concern two separate groups of scientists, namely statisticians and ecologists. However, statistical ecology has become a scientific discipline of its own, and the good use of multivariate data analysis methods by ecologists implies a fair knowledge of the mathematical properties of these methods. The organization of the book is based on ecological questions, but these questions correspond to particular classes of data analysis methods. The first chapters present both usual and multiway data analysis methods. Further chapters are dedicated for example to the analysis of spatial data, of phylogenetic structures, and of biodiversity patterns. One chapter deals with multivariate data analysis graphs. In each chapter, the basic mathematical definitions of the methods and the outputs of the R functions available in ade4 are detailed in two different boxes. The text of the book itself can be read independently from these boxes. Thus the book offers the opportunity to find information about the ecological situation from which a question raises alongside the mathematical properties of methods that can be applied to answer this question, as well as the details of software outputs. Each example and all the graphs in this book come with executable R code.

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