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eTOXlab contains a highly efficient implementation of multivariate methods like principal component analysis (PCA) and partial least squares (PLS).
In complex samples, linear regression between absorption band areas and analyte concentrations determined by a reference method are not enough to provide robust calibration; here, multivariate methods, like partial least squares (PLS) regression, have to be employed.
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Multivariate methods should, therefore, be considered instead.
Data were analyzed using univariate and multivariate methods.
The proposed discretization algorithms are incremental and multivariate methods.
The clustering is made by the use of multivariate methods.
The chemical data obtained were elaborated with statistical multivariate methods.
It can further be divided into bivariate and multivariate methods.
Agronomic potential was assessed with six descriptors and multivariate methods.
Other multivariate methods such as linear discriminant analysis (LDA) [18] or sparse logistic regression (SLR) [16] are also capable of serving as multivariate ranking methods as the SVM.
Both univariate and multivariate methods [2] have been used for classifying neuroimaging data.
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