The ELSD data were also analyzed using multivariate principal component analysis, analysis of variance, and standard least squares effects modeling.
We employed Spearman's rank correlation and multivariate principal component analysis factor analysis to identify redundancies between the assessed metrics and select the most promising ones.
Non-parametric regression and multivariate principal component analysis are used to identify the dominant and the optimum number of independent variables.
The insight of interdependency of the variables gained in non-parametric regression and multivariate principal component analysis is employed to develop an effective neural network.
Multivariate Principal Component Analysis was applied to standardized variables and a correlation table was obtained.
We determined the relationships among biological and chemical data by correlation analysis and multivariate principal component analysis (PCA).
Therefore, in addition to the presented univariate statistical solutions, an interactive multivariate principal component analysis (PCA) has been implemented within the XCMS Online platform for multigroup analysis.
Through multivariate Principal Component Analysis, in HNSCC, a positive correlation was found between immunohistochemistry MUC1 detection and Cancer Associated Serum Assay levels (Kendall τ = 0.275, p = 0.005; Fig. 2).
Multivariate principle component analysis (PCA) based on genetic similarity matrices were used to resolve the genetic relationship and overall diversity among different accessions.
Multivariate principal component analysis (PCA) of the data revealed major changes in the protein profile of 'Sunki Maravilha' in response to water deficit.
