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Determination of a multivariate detection limit and local chemical rank by designing a non‐parametric test from the zero‐component regions
Author(s) -
Liang YiZeng,
Kvalheim Olav M.,
Höskuldsson Agnar
Publication year - 1993
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.1180070406
Subject(s) - chemometrics , limit (mathematics) , multivariate statistics , detection limit , parametric statistics , zero (linguistics) , eigenvalues and eigenvectors , principal component analysis , mathematics , statistics , component (thermodynamics) , rank (graph theory) , analytical chemistry (journal) , chromatography , chemistry , physics , combinatorics , mathematical analysis , philosophy , quantum mechanics , thermodynamics , linguistics
In this paper we redefine the term detection limit to embrace the inherent multivariate nature of samples, instrumental measurements and chemometrics resolution procedures. The so‐called zero‐component regions, i.e. parts with no chemical components eluting, are used as repeated analytical blanks to estimate a statistical multivariate detection limit for determining the number of chemical species in local regions of a single two‐way chromatogram or a collection of synchronized one‐way chromatograms. For two‐way chromatography the detection limit is determined from the distribution of the first eigenvalues obtained from all possible combinations of spectra in the zero‐component regions. The number of spectra in each calculation should correspond to the number included in the later examination of the local retention time regions. For one‐way chromatography on a collection of samples with similar chemical components at varying concentrations the same procedure is used, with the samples taking the role of the spectra in two‐way chromatography. The detection limit can be chosen at various confidence levels depending on whether false positive or negative detection of minor components is most critical. The results obtained from the zero‐eigenvalue distribution are more robust than those obtained by a previously developed F ‐test.