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Numerical ecology

Author: Pierre Legendre; Louis Legendre
Publisher: Amsterdam ; Boston : Elsevier, 2012.
Series: Developments in environmental modelling, 24.
Edition/Format:   eBook : Document : English : Third English editionView all editions and formats
Database:WorldCat
Summary:
The book describes and discusses the numerical methods which are successfully being used for analysing ecological data, using a clear and comprehensive approach. These methods are derived from the fields of mathematical physics, parametric and nonparametric statistics, information theory, numerical taxonomy, archaeology, psychometry, sociometry, econometry and others. An updated, 3rd English edition of the most  Read more...
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Genre/Form: Electronic books
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Pierre Legendre; Louis Legendre
ISBN: 0444538682 9780444538680 9780444538697 0444538690
OCLC Number: 808340858
Description: 1 online resource (xvi, 990 pages) : illustrations.
Contents: Complex ecological data sets --
Matrix algebra : a summary --
Dimensional analysis in ecology --
Multidimensional quantitative data --
Multidimensional semiquantitative data --
Multidimensional qualitative data --
Ecological resemblance --
Cluster analysis --
Ordination in reduced space --
Interpretation of ecological structures --
Canonical analysis --
Ecological data series --
Spatial analysis --
Multiscale analysis : spatial eigenfunctions.
Series Title: Developments in environmental modelling, 24.
Other Titles: Ecologie numérique.
Responsibility: Pierre Legendre and Louis Legendre.

Abstract:

Describes and discusses the numerical methods which are successfully being used for analysing ecological data, using a clear and comprehensive approach. This book on quantitative analysis of  Read more...

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"Pierre Legendre.and Louis Legendre. present this text of data analysis methods for ecologists, with an emphasis on use of the statistical computer language R. The book begins by articulating salient Read more...

 
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