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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.
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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