Sensory analysis via multi-block multivariate additive PLS splines

Rosaria Lombardo, Pietro Amenta, Myrtille Vivien and Robert Sabatier

Journal of Applied Statistics, 2012, vol. 39, issue 4, 731-743

Abstract: 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.

Date: 2012
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DOI: 10.1080/02664763.2011.611239

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