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A multivariate structure with pairwise correlations instead of mutual independence allows for a better capture of multipollutant properties.
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Q-mode analysis using clustering with Type 1 SIMPROF addresses multivariate structure among samples, showing that there is clear structure associated with differences among years.
Principal Component Analysis (PCA) was performed to visualize the multivariate structure of the data sets.
Similarity profiles analysis, SIMPROF [49] was used to test for multivariate structure.
15 The multivariate structure of NMR spectral data requires appropriate statistical analysis to elucidate and interpret complex datasets with typically more variables than samples.
Such a relationship often can only be adequately described and exploited by multivariate structure-activity relationship (SAR) studies that can deal with many variables simultaneously.
A probit model structure, with assumed latent satisfaction utility model in the form of multivariate Gaussian function, was adopted for developing the preference model.
(31) and (32) proves that it may be reasonable to approximate nodal displacements of statically determinate truss structures with multivariate rational response surfaces.
The basic definitions pertaining to statistical analysis are important when dealing with more complex multivariate data structures [19 21].
In the present study, we performed a multivariate quantitative structure-activity relationship (QSAR) analysis of 52 prodiginines with antimalarial activity.
Although Negative Binomial distributions or other distributions with over-dispersion parameters are often used for modeling *-seq data, they cannot be easily adopted to model the joint distribution of multivariate signals with covariance structures.
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