Sentence examples for multivariate discriminate analysis from inspiring English sources

To evaluate the reliability of the model, the data were examined with genetic algorithm and Multivariate discriminate analysis method.

We then analyzed the morphology and size of R. oryzae s. l. spores using multivariate discriminate analysis and cluster analysis [59], [60], [61].

The output from a multivariate discriminate analysis quantifies the overall bispectral properties (frequency, power, and phase) throughout the entire frequency range.

A multivariate, discriminate analysis was performed using the following variables: PCT, PMN elastase enzyme, albumin, α-1-antitrypsin, α-2-macroglobulin, and C-reactive protein (CRP), as independent parameters.

For each character, the measurements from all specimens of a species were averaged and input into a pairwise multivariate discriminate functions analysis (DFA), as implemented in R v 2.15.1.

Multivariate discriminant analysis demonstrates the ability of the analytic variables to discriminate the vast majority of the melanocytic neoplasms, particularly when two-dimensional variables are included [ 47].

Systematic differences in metabolites between groups were identified using multivariate analysis and orthogonal partial least square discriminate analysis (OPLS-DA).

Multivariate analysis for classification was performed using partial least-squares discriminate analysis (PLS-DA) and support vector machine discriminate analysis (SVM-DA).

We then explored the hepatic metabolic profiles of AL and CR groups further by employing multivariate statistical analyses (Trygg et al., 2007), including principal component analysis (PCA) (unsupervised) and partial least-squares discriminate analysis (PLS-DA) (supervised) (Fig. 1B).

Topics include multivariate analysis of variance (MANOVA), principal components analysis, cluster analysis (hierarchical clustering, k-means), canonical correlation, multidimensional scaling ordination methods, discriminate analysis, factor analysis, and structural equations modeling.

Hence, a multivariate discriminant function analysis was conducted to determine which parameters discriminate between diabetic patients without microvascular diseases and those suffering from neuropathy, peripheral neuropathy or retinopathy.