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.
2010
Lombardo, Rosaria; Amenta, P.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/167529
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