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A distribution model of three taxa (spiders, carabid beetles, and butterflies) is related to influencing factors by means of multivariate statistics (canonical correspondence analysis (CCA), partial CCA).
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Multivariate statistics were performed on ambient data using R statistical software (R development core team, Vienna, Austria).
Univariate and multivariate statistics were considered.
The data were analyzed by multivariate statistics.
moving PCA. multivariate statistics based approaches.
Data were analyzed utilising descriptive, bivariate and multivariate statistics.
Variable selection is a venerable problem in multivariate statistics.
They can be reduced by using multivariate statistics.
One method is an analytical, small-perturbation technique using multivariate statistics.
The model is based on a novel utilization of the discriminant analysis technique of multivariate statistics.
There is also scope to improve the approach using multivariate statistics.
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