Premium
On the area of feasible solutions for rank‐deficient problems: I. Introduction of a generalized concept
Author(s) -
Sawall Mathias,
Neymeyr Klaus
Publication year - 2021
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.3316
Subject(s) - rank (graph theory) , resolution (logic) , mathematics , matrix (chemical analysis) , multivariate statistics , mathematical optimization , algorithm , computer science , statistics , combinatorics , artificial intelligence , chemistry , chromatography
Rank deficiency of a spectral data matrix means that its rank is smaller than the number of the anticipated chemical components. A rank deficiency can hide the true chemical structure of the underlying pure components and complicates the application of multivariate curve resolution and self‐modeling curve resolution techniques. A new approach for the analysis of the factor ambiguities is introduced, and the area of feasible solutions (AFS) is generalized to rank‐deficient spectral data. The extended tools are tested for the Michaelis–Menten kinetics and abstract model data.