In the last decade much effort has been spent modelling dependence among variables to probe the relationships between response variables and predictor ones observed at different occasions/spaces/times. In this paper we propose a non-linear generalization of mult-block Partial Least Squares using multivariate additive splines. We show the method performance on real sensory data sets.
Non-linear multi-block partial least squares via uni-variate and bivariate B-splines
LOMBARDO, Rosaria;
2010
Abstract
In the last decade much effort has been spent modelling dependence among variables to probe the relationships between response variables and predictor ones observed at different occasions/spaces/times. In this paper we propose a non-linear generalization of mult-block Partial Least Squares using multivariate additive splines. We show the method performance on real sensory data sets.File in questo prodotto:
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