UID:
almafu_9958115523502883
Umfang:
1 online resource (870 p.)
Ausgabe:
2nd ed.
ISBN:
9786611036430
,
1-281-03643-9
,
0-08-053787-1
,
1-281-02159-8
,
9786611021597
,
0-08-052317-X
Serie:
Developments in environmental modelling ; 20
Inhalt:
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. Compared to the first edition of Numerical Ecology, this second edition includes three new chapters, dealing with the analysis of semiquantitative data, canonical analysis and spatial analysis. New sections have been added to al
Anmerkung:
Description based upon print version of record.
,
Cover; Contents; Preface; Chapter 1. Complex ecological data sets; 1.0 Numerical analysis of ecological data; 1.1 Autocorrelation and spatial structure; 1.2 Statistical testing by permutation; 1.3 Computers; 1.4 Ecological descriptors; 1.5 Coding; 1.6 Missing data; 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 The rank of a matrix; 2.8 Matrix inversion; 2.9 Eigenvalues and eigenvectors
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2.10 Some properties of eigenvalues and eigenvectors2.11 Singular value decomposition; 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 partial correlations; 4.6 Multinormal conditional distribution
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4.7 Tests of normality and multinormalityChapter 5. Multidimensional semiquantitative data; 5.0 Nonparametric statistics; 5.1 Quantitative, semiquantitative, and qualitative multivariates; 5.2 One-dimensional nonparametric statistics; 5.3 Multidimensional ranking tests; Chapter 6. Multidimensional qualitative data; 6.0 General principles; 6.1 Information and entropy; 6.2 Two-way contingency tables; 6.3 Multiway contingency tables; 6.4 Contingency tables: correspondence; 6.5 Species diversity 235; Chapter 7. Ecological resemblance; 7.0 The basis for clustering and ordination
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7.1 Q and R analyses7.2 Association coefficients; 7.3 Q mode: similarity coefficients; 7.4 Q mode: distance coeffficients; 7.5 R mode: coeffcients of dependence; 7.6 Choice of a coef.cient; 7.7 Computer programs and packages; Chapter 8. Cluster analysis; 8.0 A search for discontinuities; 8.1 Definitions; 8.2 The basic model: single linkage clustering; 8.3 Cophenetic matrix and ultrametric property; 8.4 The panoply of methods; 8.5 Hierarchical agglomerative clustering; 8.6 Reversals; 8.7 Hierarchical divisive clustering; 8.8 Partitioning by K-means
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8.9 Species clustering: biological associations8.10 Seriation; 8.11 Clustering statistics; 8.12 Cluster validation; 8.13 Cluster representation and choice of a method; Chapter 9. Ordination in reduced space; 9.0 Projecting data sets in a few dimensions; 9.1 Principal component analysis (PCA); 9.2 Principal coordinate analysis (PCoA); 9.3 Nonmetric multidimensional scaling (MDS); 9.4 Correspondence analysis (CA); 9.5 Factor analysis; Chapter 10. Interpretation of ecological structures; 10.0 Ecological structures; 10.1 Clustering and ordination; 10.2 The mathematics of ecological interpretation
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10.3 Regression
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English
Weitere Ausg.:
ISBN 0-444-89249-4
Weitere Ausg.:
ISBN 0-444-89250-8
Sprache:
Englisch
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