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Multivariate techniques were applied to investigate the major land use sources of ion chemistry in the river.
Multivariate techniques were applied to check spatial and seasonal trends, and metals contamination sources of the Himalayan foothills streams, Pakistan.
Simple multivariate techniques were efficiently used to regress spectral features against known values of dispersed solids concentration.
Recently developed multivariate techniques were used to test for and quantify multivariate variation at different spatial scales.
Non-parametric multivariate techniques were used to assess the spatio-temporal variations on daily catch of groups of fishes throughout the study period.
Non-parametric multivariate techniques were used to classify the 88 landscape units based on presence of different biocoenoses and environmental factors.
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Several multivariate techniques are applied to interpret the grinding processes.
One of the fundamental assumptions of most parametric multivariate techniques is multivariate normality, which implies the absence of multivariate outliers.
In this study an innovative statistical procedure based on multivariate techniques is applied.
Multivariate techniques are useful in hydrogeological studies to reduce the complexity of large-scale data sets, and provide more understandable insight into the system hydrology.
The large number of objects and variables in these databases induced that besides univariate techniques, multivariate techniques are also applied to search for knowledge hidden in the data.
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