Segmented principal component transform-partial least squares regression

• Tipo: Artigo em Revista Científica Internacional
• Data: 2007

Autores

Barros, AS (Autor) Outra; Pinto, R (Autor) Outra; Delgadillo, I (Autor) Outra; Rutledge, DN (Autor) Outra

Revista

Título: Chemometrics and Intelligent Laboratory Systems

Vol. 89

Páginas: 59-68

ISSN: 0169-7439

Editora: Elsevier

Indexação

ISI Web of Knowledge - 3 Citações

Scopus - 3 Citações

Outras Informações

ID Authenticus: P-004-69H

DOI: 10.1016/j.chemolab.2007.05.009

Abstract (EN): An approach for doing PLS on very wide datasets is proposed in this work. The method is based on the decomposition, by means of a SVD, of non-superimposed segments of the original data matrix. It is shown that this approach uses less computer resources compared to SIMPLS and PCT-PLS1. Furthermore, it is also shown that the results obtained by this approach are the same as those obtained by other regression methods (PLS and SIMPLS). The method implementation is simple and can be done in a distributed environment.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 10