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To identify perinatal risk factors associated with long-term neurocognitive and behavioral impairments in children born very preterm using a multivariate, partial least squares approach.
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The aim is to develop a device for on-line estimation of production and quality variables using a multivariate statistical technique like partial least squared (PLS).
The fatty acid pattern was related to diagnostic group and intake of relevant food items using a multivariate pattern recognition method (partial least squares projections to latent structures and discriminant analysis).
We then analyzed the partial warps and uniform scores using a multivariate discriminant function analysis (DFA) based on the classification of individuals into the different spawning depths.
Experiments were designed using a multivariate approach and data were analysed using different projection methods (principal component analysis, partial least-squares).
saplings were analysed using a multivariate method.
4) Statistical classification using a multivariate Gaussian classifier.
Independent risk factors were analysed using a multivariate logistic regression.
Extraction conditions were optimized using a multivariate approach.
A very recent development is multivariate MPS in which an ensemble of variables can be simulated simultaneously using a multivariate TI.
Data were analyzed using a multivariate analysis of variance (MANOVA).
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