Regression of a data matrix on descriptors of both its rows and of its columns via latent variables: L-PLSR

Article ID	Journal	Published Year	Pages	File Type
10327722	Computational Statistics & Data Analysis	2005	21 Pages	PDF

Abstract

The method is applied to the analysis of consumer liking data Y of six products assessed by 125 persons, in light of 10 other product descriptors X and 15 other person descriptors Z. Its performance is also checked on artificial data.

Keywords

PLS PLSR SVD L-PLSR singular value decomposition Partial least squares Eigenvector Regression Latent variables Multivariate

Related Topics

Physical Sciences and Engineering Computer Science Computational Theory and Mathematics

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Regression of a data matrix on descriptors of both its rows and of its columns via latent variables: L-PLSR

Authors

Harald Martens, Endre Anderssen, Arnar Flatberg, Lars Halvor Gidskehaug, Martin HÃ¸y, Frank Westad, Anette Thybo, Magni Martens,