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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Complex ecological data sets
Matrix algebra a summary
Dimensional analysis in ecology
Multidimensional quantitative data
Multidimensional semiquantitative data
Multidimensional qualitative data
Ordination in reduced space
algorithm association autocorrelation axis binary biplot calculation canonical analysis centroids Chapter columns 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 equal equation estimate Euclidean distance explained explanatory variables F-statistic fraction frequency function gradient graph groups Legendre linear regression Mantel test measure methods multidimensional multiple regression multivariate normal null hypothesis Numerical example objects observations obtained ordination orthogonal package pairs parameters partial PCoA periodogram permutation test plot polynomial presence-absence principal component analysis produce qualitative descriptors quantitative random reduced space relationships represented residuals response variable rows sampling scaling Section similarity spatial correlation spatial structure species abundance statistic Subsection sum of squares symmetric tests of significance transformation values variance variogram vector zero