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Use of double windowing, variable selection, variable ranking and resolvability indices in window factor analysis
Author(s) -
Brereton Richard G.,
Elbergali Abdallah K.
Publication year - 1994
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.1180080607
Subject(s) - window (computing) , ranking (information retrieval) , mathematics , variable (mathematics) , resolution (logic) , statistics , eigenvalues and eigenvectors , selection (genetic algorithm) , data matrix , matrix (chemical analysis) , algorithm , computer science , artificial intelligence , physics , mathematical analysis , materials science , chemistry , clade , biochemistry , quantum mechanics , phylogenetic tree , gene , operating system , composite material
Abstract A method for selecting variables in the non‐sequential direction of a two‐way data matrix (e.g. wavelength in diode array HPLC) is described. Composition 1 and 2 resolvability indices are calculated according to the size of eigenvalues of uncentred data matrices as a window is moved along the sequential direction. A double‐window technique is then performed where resolvability indices are calculated as a window is moved along the non‐sequential direction. Some regions have higher resolvability indices and hence are more useful for resolution. Variables are ranked according to resolvability. Two simulations are analysed and it is shown that it is possible to obtain good resolution on a small subset of the original variables.