Numerical Ecology, Volumen 24Elsevier, 6 ago 2012 - 990 páginas 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.
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Índice
Complex ecological data sets | 1 |
Matrix algebra a summary | 59 |
Dimensional analysis in ecology | 109 |
Multidimensional quantitative data | 143 |
Multidimensional semiquantitative data | 195 |
Multidimensional qualitative data | 219 |
Ecological resemblance | 265 |
Cluster analysis | 337 |
Interpretation of ecological structures | 521 |
Canonical analysis | 625 |
Ecological data series | 711 |
Spatial analysis | 785 |
Multiscale analysis spatial eigenfunctions | 859 |
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| 969 | |
Ordination in reduced space | 425 |
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Términos y frases comunes
algorithm association autocorrelation axis binary biplot calculation canonical analysis centroids Chapter columns community composition computed contingency table correlation coefficient correlogram correspondence analysis covariance data matrix data series data sets dbMEM dendrogram described detrended diagonal dimensional distance classes distance matrix distribution Ecological application ecological data ecologists eigenfunctions eigenvalues eigenvectors environmental variables equation estimate Euclidean distance explained explanatory variables fraction frequency function gradient graph groups Legendre linear Mantel test measure methods multidimensional multiple regression multivariate normal null hypothesis Numerical example objects observations obtained ordination orthogonal package pairs parameters partial partitioning PCoA periodogram permutation test plot polynomial presence-absence principal component analysis principal coordinate produce qualitative descriptors quantitative random reduced space relationships represented residuals response variable rows sampling scaling Section similarity spatial correlation spatial structure statistic Subsection sum of squares symmetric transformation values variance variation variogram vector zero