Maximum Likelihood Principal Component Analysis as initial projection step in Multivariate Curve Resolution analysis of noisy data

Article ID	Journal	Published Year	Pages	File Type
7563465	Chemometrics and Intelligent Laboratory Systems	2012	8 Pages	PDF

Abstract

âº A comparison between MCR-ALS, MCR-WALS and MLPCA-MCR-ALS, is presented. âº Simulated data with different error structures were used for this study. âº Solutions obtained by MLPCA-MCR-ALS and MCR-WALS are practically identical.

Keywords

Alternating least squares Noisy data Error structure Multivariate curve resolution

Related Topics

Physical Sciences and Engineering Chemistry Analytical Chemistry

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Maximum Likelihood Principal Component Analysis as initial projection step in Multivariate Curve Resolution analysis of noisy data

Authors

Mahsa Dadashi, Hamid Abdollahi, RomÃ Tauler,