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dc.contributor.author
Olivieri, Alejandro Cesar  
dc.contributor.author
Allegrini, Franco  
dc.contributor.other
Brown, Steven  
dc.contributor.other
Tauler, Romà  
dc.contributor.other
Walczak, Beata  
dc.date.available
2021-08-31T01:45:31Z  
dc.date.issued
2020  
dc.identifier.citation
Olivieri, Alejandro Cesar; Allegrini, Franco; Figures of Merit; Elsevier; 2; 2020; 441-463  
dc.identifier.isbn
978-0444641656  
dc.identifier.uri
http://hdl.handle.net/11336/139268  
dc.description.abstract
Figures of merit are numerical parameters, usually employed for comparing analytical methods in terms of predictive ability and detection capabilities. The estimation of analytical figures of merit for calibrations based on first- and higher-order data has become an active research field in recent years. The starting approach was to extend the well-known univariate calibration concepts todata of increasing complexity. For example, the sensitivity, which is a key figure of merit for qualifying analytical methods, is correctly interpreted in the framework of classical univariate calibration as the change in response (the analytical signal) for a given change in stimulus (the analyte concentration). This concept was extended to multivariate and multi-way calibration using the net analyte signal (NAS) as an analogue of the raw instrumental signal in univariate calibration.5,6 The notion of net analyte signal is attractive, because it measures, in principle, the portion of the overall signal which can be directly employed to quantitate a givenanalyte in the presence of interferents. However, this approach proved to be unsuccessful to estimate the sensitivity, particularly in multi-way calibration.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Elsevier  
dc.rights
info:eu-repo/semantics/restrictedAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
QUIMIOMETRÍA  
dc.subject
QUIMICA ANALITICA  
dc.subject
CIFRAS DE MERITO  
dc.subject.classification
Química Analítica  
dc.subject.classification
Ciencias Químicas  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Figures of Merit  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.type
info:eu-repo/semantics/bookPart  
dc.type
info:ar-repo/semantics/parte de libro  
dc.date.updated
2021-06-07T16:10:41Z  
dc.journal.volume
2  
dc.journal.pagination
441-463  
dc.journal.pais
Países Bajos  
dc.journal.ciudad
Amsterdam  
dc.description.fil
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  
dc.description.fil
Fil: Allegrini, Franco. 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  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://doi.org/10.1016/B978-0-12-409547-2.14612-8  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/B9780124095472146128  
dc.conicet.paginas
2944  
dc.source.titulo
Comprehensive Chemometrics: Chemical and Biochemical Data Analysis  
dc.conicet.nroedicion
2