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The methodology introduced an iterative multivariate data analysis to examine the effects of rust steel descriptors, that is, texture and color distribution on a set of classifier algorithms.
Iterative multivariate statistical analysis (MSA) and multi-reference alignment (MRA) of the extracted particles provided representative 2D views of the PRC2 complex, which served as templates for all subsequent automated particle selection.
Variables that were found to be significant (P < 0.05) in univariate analysis were included in a multivariate analysis, using a stepwise iterative procedure.
These analyses were performed in an iterative, back and forth process between descriptive or bivariate analysis and multivariate analysis.
Data were then used for multivariate pattern analysis employing a method that combines machine learning with an iterative, multivariate voxel selection algorithm.
Analysis of incomplete multivariate analysis.
Principal components and multivariate analysis.
Methods of Multivariate Analysis vol. 2. John Wiley: Hoboken, NJ, 2002.
A new method for non-parametric multivariate analysis of variance.
The multivariate analysis... indicates that heads of poor families should average $2,204 in earnings.
Multivariate Analysis and Random Matrices in Statistics.
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