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The PLS model space revisited
Author(s) -
Wold Svante,
Høy Martin,
Martens Harald,
Trygg Johan,
Westad Frank,
MacGregor John,
Wise Barry M.
Publication year - 2009
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1171
Subject(s) - space (punctuation) , latent variable , mathematics , variable (mathematics) , computer science , algorithm , statistics , artificial intelligence , mathematical analysis , operating system
Pell, Ramos and Manne (PRM) in a recent article in this journal claim that the ‘conventional’ PLS algorithm with orthogonal scores has an inherent inconsistency in that it uses different model spaces for calculating the prediction model coefficients and for calculating the X ‐space model and it's residuals [1]. We disagree with PRM. All PLS model scores, residuals, coefficients, etc., obtained by the conventional PLS algorithm do come from the same underlying latent variable (LV) model, and not from different models or model spaces as PRM suggest. PRM have simply posed a different model with different assumptions and obtained slightly different results, as should have been expected. Copyright © 2008 John Wiley & Sons, Ltd.