The effect of data matrix augmentation and constraints in extended multivariate curve resolution–alternating least squares

Autores
Olivieri, Alejandro Cesar; Tauler, Romà
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The reliability of results obtained by multivariate curve resolution (MCR) methods is strongly dependent on the absence or presence of a small degree of rotational ambiguity associated to them. In this work, the effect of rotational ambiguities on the profiles resolved by MCR methods is examined in detail for cases of interest to analytical chemistry, where a number of calibration samples are usually prepared containing analyte standards, while test samples may contain additional uncalibrated constituents. These multiple chemical data sets having common constituents are simultaneously analyzed using matrix augmentation strategies. In these cases, conditions for better resolution and improved profiles are more easily achieved. To evaluate the extension of rotational ambiguities and to quantify their reduction after matrix augmentation, we applied the MCR-BANDS procedure. Results obtained by the application of this procedure confirmed that the simultaneous analysis of multiple data sets decreased considerably the extension of rotational ambiguities compared with those obtained when only a single data set is analyzed. Simulated and experimental data sets of interest to second-order analytical calibration are discussed.
Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Tauler, Romà. Consejo Superior de Investigaciones Científicas; España
Materia
Data Matrix Augmentation
Mixture Analysis with Extended Mcr
Multivariate Curve Resolution
Rotational Ambiguity And Feasible Solutions
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/63828
Acceder
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network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling The effect of data matrix augmentation and constraints in extended multivariate curve resolution–alternating least squaresOlivieri, Alejandro CesarTauler, RomàData Matrix AugmentationMixture Analysis with Extended McrMultivariate Curve ResolutionRotational Ambiguity And Feasible Solutionshttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1The reliability of results obtained by multivariate curve resolution (MCR) methods is strongly dependent on the absence or presence of a small degree of rotational ambiguity associated to them. In this work, the effect of rotational ambiguities on the profiles resolved by MCR methods is examined in detail for cases of interest to analytical chemistry, where a number of calibration samples are usually prepared containing analyte standards, while test samples may contain additional uncalibrated constituents. These multiple chemical data sets having common constituents are simultaneously analyzed using matrix augmentation strategies. In these cases, conditions for better resolution and improved profiles are more easily achieved. To evaluate the extension of rotational ambiguities and to quantify their reduction after matrix augmentation, we applied the MCR-BANDS procedure. Results obtained by the application of this procedure confirmed that the simultaneous analysis of multiple data sets decreased considerably the extension of rotational ambiguities compared with those obtained when only a single data set is analyzed. Simulated and experimental data sets of interest to second-order analytical calibration are discussed.Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; ArgentinaFil: Tauler, Romà. Consejo Superior de Investigaciones Científicas; EspañaJohn Wiley & Sons Ltd2017-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/63828Olivieri, Alejandro Cesar; Tauler, Romà; The effect of data matrix augmentation and constraints in extended multivariate curve resolution–alternating least squares; John Wiley & Sons Ltd; Journal Of Chemometrics; 31; 3; 3-2017; 1-10; e28750886-9383CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1002/cem.2875info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1002/cem.2875info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:44:08Zoai:ri.conicet.gov.ar:11336/63828instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:44:08.455CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv The effect of data matrix augmentation and constraints in extended multivariate curve resolution–alternating least squares
title The effect of data matrix augmentation and constraints in extended multivariate curve resolution–alternating least squares
spellingShingle The effect of data matrix augmentation and constraints in extended multivariate curve resolution–alternating least squares
Olivieri, Alejandro Cesar
Data Matrix Augmentation
Mixture Analysis with Extended Mcr
Multivariate Curve Resolution
Rotational Ambiguity And Feasible Solutions
title_short The effect of data matrix augmentation and constraints in extended multivariate curve resolution–alternating least squares
title_full The effect of data matrix augmentation and constraints in extended multivariate curve resolution–alternating least squares
title_fullStr The effect of data matrix augmentation and constraints in extended multivariate curve resolution–alternating least squares
title_full_unstemmed The effect of data matrix augmentation and constraints in extended multivariate curve resolution–alternating least squares
title_sort The effect of data matrix augmentation and constraints in extended multivariate curve resolution–alternating least squares
dc.creator.none.fl_str_mv Olivieri, Alejandro Cesar
Tauler, Romà
author Olivieri, Alejandro Cesar
author_facet Olivieri, Alejandro Cesar
Tauler, Romà
author_role author
author2 Tauler, Romà
author2_role author
dc.subject.none.fl_str_mv Data Matrix Augmentation
Mixture Analysis with Extended Mcr
Multivariate Curve Resolution
Rotational Ambiguity And Feasible Solutions
topic Data Matrix Augmentation
Mixture Analysis with Extended Mcr
Multivariate Curve Resolution
Rotational Ambiguity And Feasible Solutions
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The reliability of results obtained by multivariate curve resolution (MCR) methods is strongly dependent on the absence or presence of a small degree of rotational ambiguity associated to them. In this work, the effect of rotational ambiguities on the profiles resolved by MCR methods is examined in detail for cases of interest to analytical chemistry, where a number of calibration samples are usually prepared containing analyte standards, while test samples may contain additional uncalibrated constituents. These multiple chemical data sets having common constituents are simultaneously analyzed using matrix augmentation strategies. In these cases, conditions for better resolution and improved profiles are more easily achieved. To evaluate the extension of rotational ambiguities and to quantify their reduction after matrix augmentation, we applied the MCR-BANDS procedure. Results obtained by the application of this procedure confirmed that the simultaneous analysis of multiple data sets decreased considerably the extension of rotational ambiguities compared with those obtained when only a single data set is analyzed. Simulated and experimental data sets of interest to second-order analytical calibration are discussed.
Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Tauler, Romà. Consejo Superior de Investigaciones Científicas; España
description The reliability of results obtained by multivariate curve resolution (MCR) methods is strongly dependent on the absence or presence of a small degree of rotational ambiguity associated to them. In this work, the effect of rotational ambiguities on the profiles resolved by MCR methods is examined in detail for cases of interest to analytical chemistry, where a number of calibration samples are usually prepared containing analyte standards, while test samples may contain additional uncalibrated constituents. These multiple chemical data sets having common constituents are simultaneously analyzed using matrix augmentation strategies. In these cases, conditions for better resolution and improved profiles are more easily achieved. To evaluate the extension of rotational ambiguities and to quantify their reduction after matrix augmentation, we applied the MCR-BANDS procedure. Results obtained by the application of this procedure confirmed that the simultaneous analysis of multiple data sets decreased considerably the extension of rotational ambiguities compared with those obtained when only a single data set is analyzed. Simulated and experimental data sets of interest to second-order analytical calibration are discussed.
publishDate 2017
dc.date.none.fl_str_mv 2017-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/63828
Olivieri, Alejandro Cesar; Tauler, Romà; The effect of data matrix augmentation and constraints in extended multivariate curve resolution–alternating least squares; John Wiley & Sons Ltd; Journal Of Chemometrics; 31; 3; 3-2017; 1-10; e2875
0886-9383
CONICET Digital
CONICET
url http://hdl.handle.net/11336/63828
identifier_str_mv Olivieri, Alejandro Cesar; Tauler, Romà; The effect of data matrix augmentation and constraints in extended multivariate curve resolution–alternating least squares; John Wiley & Sons Ltd; Journal Of Chemometrics; 31; 3; 3-2017; 1-10; e2875
0886-9383
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1002/cem.2875
info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1002/cem.2875
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv John Wiley & Sons Ltd
publisher.none.fl_str_mv John Wiley & Sons Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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