Abstract
In this article, the extension of the Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) method to the simultaneous analysis of multiple data sets bearing information in common is presented. The basic assumption in this extension of MCR methods is the fulfillment of a common bilinear model for the simultaneously analyzed data sets, which implies that they share some parts of their data variance at least, e.g. some chemical components or species are common among them. Different data arrangements are possible in this approach, depending on the common information shared among the different simultaneously analyzed data sets. Recently, a new incomplete multiset arrangement has been proposed that allows handling missing blocks of information in row- and column-wise augmented multisets as well.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Reference Module in Chemistry, Molecular Sciences and Chemical Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
