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Selectivity, local rank, three‐way data analysis and ambiguity in multivariate curve resolution
Author(s) -
Tauler Romà,
Smilde Age,
Kowalski Bruce
Publication year - 1995
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.1180090105
Subject(s) - multivariate statistics , resolution (logic) , ambiguity , rank (graph theory) , ambiguity resolution , multivariate analysis , uniqueness , focus (optics) , mathematics , curve fitting , computer science , statistics , algorithm , artificial intelligence , mathematical analysis , combinatorics , optics , physics , telecommunications , gnss applications , global positioning system , programming language
A new multivariate curve resolution method is presented and tested with data of various levels of complexity. Rotational and intensity ambiguities and the effect of selectivity on resolution are the focus. Analysis of simulated data provides the general guidelines concerning the conditions for uniqueness of a solution for a given problem. Multivariate curve resolution is extended to the analysis of three‐way data matrices. The particular case of three‐way data where only one of the orders is common between slices is studied in some detail.