Title Statements
- Full title :Numerical ecology / Pierre Legendre, Louis Legendre.
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 widely cited book on quantitative analysis of multivariate ecological dataRelates ecological questions to methods of statistical analysis, with a clear descripti.
Read More ↓Edition Statements
- Publication Date:2012.
- Edition:3rd ed
Publication Statements
- Publisher(s):Elsevier
- Place of Publication:Oxford
- Language:eng
- Publication Date:2012.
The Physical Object
- Description:1 online resource (xvi, 990 pages) : : illustrations
Edition Identifiers
- ISBN:0444538690, 9780444538697, 9780444538680, 0444538682
- oclc:ocn860504195
- LC Classification:QH541.15.M34 L4313 2012
- Dewey Decimal:577.0151
Table of Contents
Front Cover; Numerical Ecology; Copyright; Contents; Preface; Chapter 1: Complex ecological data sets; 1.0 Numerical analysis of ecological data; 1.1 Spatial structure, spatial dependence, spatial correlation; 1.2 Statistical testing by permutation; 1.3 Computer programs and packages; 1.4 Ecological descriptors; 1.5 Coding; 1.6 Missing data; 1.7 Software; Chapter 2: Matrix algebra: a summary; 2.0 Matrix algebra; 2.1 The ecological data matrix; 2.2 Association matrices; 2.3 Special matrices; 2.4 Vectors and scaling; 2.5 Matrix addition and multiplication; 2.6 Determinant; 2.7 Rank of a matrix.
2.8 Matrix inversion2.9 Eigenvalues and eigenvectors; 2.10 Some properties of eigenvalues and eigenvectors; 2.11 Singular value decomposition; 2.12 Software; Chapter 3: Dimensional analysis in ecology; 3.0 Dimensional analysis; 3.1 Dimensions; 3.2 Fundamental principles and the Pi theorem; 3.3 The complete set of dimensionless products; 3.4 Scale factors and models; Chapter 4: Multidimensional quantitative data; 4.0 Multidimensional statistics; 4.1 Multidimensional variables and dispersion matrix; 4.2 Correlation matrix; 4.3 Multinormal distribution; 4.4 Principal axes.
4.5 Multiple and par…
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