Second-order and higher-order multivariate calibration methods applied to non-multilinear data using different algorithms

We discuss and evaluate the current state of second-order and higher-order multivariate calibration methods devoted to the determination of compounds in non-multilinear data systems. We examine possible causes of multilinearity deviations: (1) a non-linear relationship between signal and analyte con...

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Published inTrAC, Trends in analytical chemistry (Regular ed.) Vol. 30; no. 4; pp. 607 - 617
Main Authors Olivieri, A.C., Escandar, G.M., Peña, A. Muñoz de la
Format Journal Article
LanguageEnglish
Published Kidlington Elsevier B.V 01.04.2011
Elsevier
Subjects
Algorithm
algorithms
Analyte
Analytical chemistry
Applied sciences
Biological sample
calibration
Chemistry
Component profile
Concentration
Determination
Environmental sample
Exact sciences and technology
Global environmental pollution
Multilinearity deviation
Multivariate calibration method
Non-multilinear data
Pollution
Analyte
Biological sample
Multilinearity deviation
Non-multilinear data
Environmental sample
Multivariate calibration method
Component profile
Concentration
Determination
Algorithm
Second order
Sample
Review
Calibration
Method
Multivariate analysis
Biological compound
Signal
Cover
Limitation
Environment
Online AccessGet full text
ISSN0165-9936
1879-3142
DOI10.1016/j.trac.2010.11.018

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Abstract We discuss and evaluate the current state of second-order and higher-order multivariate calibration methods devoted to the determination of compounds in non-multilinear data systems. We examine possible causes of multilinearity deviations: (1) a non-linear relationship between signal and analyte concentration; (2) a signal for a given sample that is non-multilinear; and, (3) component profiles that are not constant across the different samples. We discuss the advantages and the limitations of the algorithms available to cope with these different situations. The review covers relevant analytical problems found in samples of environmental and biological interest, highlighting some significant examples, and evaluating the advantages and the limitations of the different algorithms available.
AbstractList We discuss and evaluate the current state of second-order and higher-order multivariate calibration methods devoted to the determination of compounds in non-multilinear data systems. We examine possible causes of multilinearity deviations: We discuss the advantages and the limitations of the algorithms available to cope with these different situations. The review covers relevant analytical problems found in samples of environmental and biological interest, highlighting some significant examples, and evaluating the advantages and the limitations of the different algorithms available.
We discuss and evaluate the current state of second-order and higher-order multivariate calibration methods devoted to the determination of compounds in non-multilinear data systems. We examine possible causes of multilinearity deviations: (1) a non-linear relationship between signal and analyte concentration; (2) a signal for a given sample that is non-multilinear; and, (3) component profiles that are not constant across the different samples. We discuss the advantages and the limitations of the algorithms available to cope with these different situations. The review covers relevant analytical problems found in samples of environmental and biological interest, highlighting some significant examples, and evaluating the advantages and the limitations of the different algorithms available.
Author Olivieri, A.C.
Peña, A. Muñoz de la
Escandar, G.M.
Author_xml – sequence: 1
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  surname: Olivieri
  fullname: Olivieri, A.C.
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  givenname: G.M.
  surname: Escandar
  fullname: Escandar, G.M.
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  givenname: A. Muñoz de la
  surname: Peña
  fullname: Peña, A. Muñoz de la
  organization: Departamento de Química Analítica, Facultad de Ciencias, Universidad de Extremadura, 06071 Badajoz, España
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Issue 4
Keywords Analyte
Biological sample
Multilinearity deviation
Non-multilinear data
Environmental sample
Multivariate calibration method
Component profile
Concentration
Determination
Algorithm
Second order
Sample
Review
Calibration
Method
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Biological compound
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SubjectTerms Algorithm
algorithms
Analyte
Analytical chemistry
Applied sciences
Biological sample
calibration
Chemistry
Component profile
Concentration
Determination
Environmental sample
Exact sciences and technology
Global environmental pollution
Multilinearity deviation
Multivariate calibration method
Non-multilinear data
Pollution
Title Second-order and higher-order multivariate calibration methods applied to non-multilinear data using different algorithms
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