Sensory analysis via multi-block multivariate additive PLS splines
In the last decade, much effort has been spent on modelling dependence between sensory variables and chemical--physical ones, especially when observed at different occasions/spaces/times or if collected from several groups (blocks) of variables. In this paper, we propose a nonlinear generalization of multi-block partial least squares with the inclusion of variable interactions. We show the performance of the method on a known data set.
Volume (Year): 39 (2012)
Issue (Month): 4 (August)
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