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
abundance analysis approach association axes axis calculation called canonical Chapter clustering coefficient columns compared computed considered contains coordinates correlation corresponding covariance data sets dependence described descriptors determine discussed distance distribution ecological effect eigenfunctions eigenvalues eigenvectors environmental equal equation estimate Euclidean example explained explanatory variables Figure fitted fraction frequency function given groups hypothesis included independent indices interpretation Legendre length linear matrix mean measure methods multiple multivariate normal Numerical example objects observations obtained original package pairs partial partitioning period permutation plot points positive possible present principal component problem produce provides quantitative random reference regression relationships represented respect response rows sampling scaling Section shown shows significance similarity single space spatial species square standard statistic step structure Subsection Table transformation units values variables variance variation vector weights