TY  - BOOK
AU  - Legendre,Pierre
AU  - Legendre,Louis
AU  - Legendre,Louis
TI  - Numerical ecology
T2  - Developments in environmental modelling
SN  - 9780444892492
AV  - QH541.15.M34 L4313 1998eb
U1  - 577/.01/51 22
PY  - 1998///
CY  - Amsterdam, New York
PB  - Elsevier
KW  - Ecology
KW  - Mathematics
KW  - Écologie
KW  - Mathématiques
KW  - Ecologie
KW  - gtt
KW  - Data-analyse
KW  - Statistische methoden
KW  - Science
KW  - Natural history
KW  - SCIENCE
KW  - Environmental Science (see also Chemistry
KW  - Environmental)
KW  - bisacsh
KW  - NATURE
KW  - Ecosystems & Habitats
KW  - Wilderness
KW  - Life Sciences
KW  - fast
KW  - Electronic books
N1  - Rev. edition of: Ecologie numérique / Louis Legendre. 1983; Includes bibliographical references (p. 787-832) and index; Chapter headings and selected parts: Preface. Complex Ecological Data Sets. Numerical analysis of ecological data. Statistical testing by permutation. Ecological descriptors. Matrix Algebra: A Summary. The ecological data matrix. Vectors and scaling. Eigenvalues and eigenvectors. Dimensional Analysis in Ecology. Fundamental principles and the Pi theorem. Scale factors and models. Multidimensional Quantitative Data. Multidimensional variables and dispersion matrix. Multinormal distribution. Tests of normality and multinormality. Multidimensional Semiquantitative data. Nonparametric statistics. Quantitative, semiquantitative, and qualitative multivariates. Multidimensional Qualitative Data. Multiway contingency tables. Species diversity. Ecological Resemblance. The basis for clustering and ordination. Association coefficients. R mode: coefficients of dependence. Cluster Analysis. The basic model: single linkage clustering. Cophenetic matrix and ultrametric property. Hierarchical divisive clustering. Ordination in Reduced Space. Projecting data sets in a few dimensions. Principal component analysis (PCA). Nonmetric multidimensional scaling (MDS). Interpretation of Ecological Structures. Ecological structures. The mathematics of ecological interpretation. The 4th-corner problem. Canonical Analysis. Redundancy analysis (RDA). Canonical correspondence analysis (CCA). Canonical analysis of species data. Ecological Data Series. Characteristics of data series and research objectives. Trend extraction and numerical filters. Periodic variabilty: spectral analysis. Detection of discontinuities on multivariate series. Box-Jenkins models. Spatial Analysis. Unconstrained and constrained ordination maps. Causal modelling: partial canonical analysis. Causal modelling: partial Mantel analysis. Bibliography. Tables. Subject index
N2  - 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 almost all other chapters. There are sections listing available computer programs and packages at the end of several chapters. As in the previous English and French editions, there are numerous examples from the ecological literature, and the choice of methods is facilitated by several synoptic tables
UR  - http://www.sciencedirect.com/science/book/9780444892492
ER  -