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The second approach is based on multivariate analysis techniques that probe the compatibility of the candidate events with the signal.
Different multivariate analysis techniques were used for classification of the snack groups.
It is based on statistical multivariate analysis techniques, Principal Components Analysis and Cluster Analysis.
Principal component analysis and partial least squares regression were applied as the multivariate analysis techniques.
The potential power of multivariate analysis techniques for correlating Raman spectra and polymer morphology was clearly demonstrated.
The results provide a foundation for the application of multivariate analysis techniques to identify different structures that develop in metal cation exchanged Nafion during changes in hydration state.
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Image features are extracted with a multivariate analysis technique from RGB pictures.
To extract trends from within the complex ToF-SIMS dataset, a multivariate analysis technique, principal component analysis (PCA), was employed.
This study outlines the use of a statistical multivariate analysis technique and applying it to develop a reliable model for the maximum displacement capacity prediction of RMSW systems.
Accordingly, at the stage of designing or analyzing a study, confounding should be controlled with a restriction, matching, stratified or multivariate analysis technique.
SEM is defined as very powerful multivariate analysis technique which includes specialized versions of a number of other analysis methods as particular cases (Shah and Goldstein 2006).
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