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 nonlinear generalization of multi-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 Univariate and Bivariate B-splines

Amenta P.
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 nonlinear generalization of multi-block Partial Least Squares using multivariate additive splines. We show the method performance on real sensory data sets.
88-901015-8-X
multivariate additive partial least squares; B-splines; multi-block analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12070/7180
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