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.

Sensory analysis via multi-block multivariate additive PLS splines

Amenta P;
2012

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.
multivariate additive partial least-squares splines; multi-block analysis; sensorial and chemical–physical variables
File in questo prodotto:
File Dimensione Formato  
Sensory analysis via multi-block multivariate additive PLS splines.pdf

non disponibili

Licenza: Non specificato
Dimensione 359.75 kB
Formato Adobe PDF
359.75 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12070/2664
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
social impact