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Kernel-Partial Least Squares regression coupled to pseudo-sample trajectories for the analysis of mixture designs of experiments

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Kernel-Partial Least Squares regression coupled to pseudo-sample trajectories for the analysis of mixture designs of experiments

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Vitale, R.; Palací-López, DG.; Kerkenaar, H.; Postma, G.; Buydens, L.; Ferrer, A. (2018). Kernel-Partial Least Squares regression coupled to pseudo-sample trajectories for the analysis of mixture designs of experiments. Chemometrics and Intelligent Laboratory Systems. 175:37-46. https://doi.org/10.1016/j.chemolab.2018.02.002

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/133377

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Title: Kernel-Partial Least Squares regression coupled to pseudo-sample trajectories for the analysis of mixture designs of experiments
Author: Vitale, Raffaele Palací-López, Daniel Gonzalo Kerkenaar, Harmen Postma, GJ Buydens, Lutgarde Ferrer, Alberto
UPV Unit: Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat
Issued date:
Abstract:
[EN] This article explores the potential of Kernel-Partial Least Squares (K-PLS) regression for the analysis of data proceeding from mixture designs of experiments. Gower's idea of pseudo-sample trajectories is exploited ...[+]
Subjects: Mixture designs of experiments , Kernel-Partial Least Squares (K-PLS) , Pseudo-sample trajectories , Scheffe and Cox polynomials , Partial Least Squares (PLS) , Ordinary Least Squares (OLS)
Copyrigths: Reserva de todos los derechos
Source:
Chemometrics and Intelligent Laboratory Systems. (issn: 0169-7439 )
DOI: 10.1016/j.chemolab.2018.02.002
Publisher:
Elsevier
Publisher version: https://doi.org/10.1016/j.chemolab.2018.02.002
Project ID:
info:eu-repo/grantAgreement/MINECO//DPI2014-55276-C5-1-R/ES/BIOLOGIA SINTETICA PARA LA MEJORA EN BIOPRODUCCION: DISEÑO, OPTIMIZACION, MONITORIZACION Y CONTROL/
Thanks:
This research work was partially supported by the Spanish Ministry of Economy and Competitiveness under the project DPI2014-55276-C5-1R and Shell Global Solutions International B.V. (Amsterdam, The Netherlands).
Type: Artículo

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