Cokriging of compositional balances including a dimension reduction and retrieval of original units

Compositional data constitutes a special class of quantitative measurements involving parts of a whole. The sample space has an algebraic-geometric structure different from that of real-valued data. A subcomposition is a subset of all possible parts. When compositional data values include geographic...

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Detalles Bibliográficos
Autores: Pawlowsky-Glahn, Vera, Egozcue, Juan José, Olea, Ricardo A., Pardo-Igúzquiza, Eulogio
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/13738
Acceso en línea:http://hdl.handle.net/10256/13738
Access Level:acceso abierto
Palabra clave:Geologia -- Mètodes estadístics
Geology -- Statistical methods
Correlació (Estadística)
Correlation (Statistics)
Geoquímica
Geochemistry
Anàlisi multivariable
Multivariate analysis
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spelling Cokriging of compositional balances including a dimension reduction and retrieval of original unitsPawlowsky-Glahn, VeraEgozcue, Juan JoséOlea, Ricardo A.Pardo-Igúzquiza, EulogioGeologia -- Mètodes estadísticsGeology -- Statistical methodsCorrelació (Estadística)Correlation (Statistics)GeoquímicaGeochemistryAnàlisi multivariableMultivariate analysisCompositional data constitutes a special class of quantitative measurements involving parts of a whole. The sample space has an algebraic-geometric structure different from that of real-valued data. A subcomposition is a subset of all possible parts. When compositional data values include geographical locations, they are also regionalized variables. In the Earth sciences, geochemical analyses are a common form of regionalized compositional data. Ordinarily, there are measurements only at data locations. Geostatistics has proven to be the standard for spatial estimation of regionalized variables but, in general, the compositional character of the geochemical data has been ignored. This paper presents in detail an application of cokriging for the modelling of compositional data using a method that is consistent with the compositional character of the data. The uncertainty is evaluated by a Monte Carlo procedure. The method is illustrated for the contents of arsenic and iron in groundwaters in Bangladesh, which have the peculiarity of being measured in milligrams per litre, units for which the sum of all parts does not add to a constant. Practical results include maps of estimates of the geochemical elements in the original concentration units, as well as measures of uncertainty, such as the probability that the concentration may exceed a given threshold. Results indicate that probabilities of exceedance in previous studies of the same data are too lowThis research has been partly supported by the Spanish Ministry of Economy and Competitiveness under the project METRICS (Ref. MTM2012-33236); and by the Agencia de Gestió d’Ajuts Universitaris i de Recerca of the Generalitat de Catalunya under project Ref: 2009SGR424Southern African Institute of Mining and Metallurgy (SAIMM)Ministerio de Ciencia e Innovación (Espanya)2015info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10256/13738http://hdl.handle.net/10256/13738The Journal of The Southern African Institute of Mining and Metallurgy, 2015, vol. 115, p.59-72Articles publicats (D-IMA)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)Inglésinfo:eu-repo/semantics/altIdentifier/issn/2225-6253info:eu-repo/semantics/altIdentifier/eissn/2411-9717info:eu-repo/grantAgreement/MINECO//MTM2012-33236Attribution 3.0 Spainhttp://creativecommons.org/licenses/by/4.0/es/info:eu-repo/semantics/openAccessoai:recercat.cat:10256/137382026-05-29T05:05:01Z
dc.title.none.fl_str_mv Cokriging of compositional balances including a dimension reduction and retrieval of original units
title Cokriging of compositional balances including a dimension reduction and retrieval of original units
spellingShingle Cokriging of compositional balances including a dimension reduction and retrieval of original units
Pawlowsky-Glahn, Vera
Geologia -- Mètodes estadístics
Geology -- Statistical methods
Correlació (Estadística)
Correlation (Statistics)
Geoquímica
Geochemistry
Anàlisi multivariable
Multivariate analysis
title_short Cokriging of compositional balances including a dimension reduction and retrieval of original units
title_full Cokriging of compositional balances including a dimension reduction and retrieval of original units
title_fullStr Cokriging of compositional balances including a dimension reduction and retrieval of original units
title_full_unstemmed Cokriging of compositional balances including a dimension reduction and retrieval of original units
title_sort Cokriging of compositional balances including a dimension reduction and retrieval of original units
dc.creator.none.fl_str_mv Pawlowsky-Glahn, Vera
Egozcue, Juan José
Olea, Ricardo A.
Pardo-Igúzquiza, Eulogio
author Pawlowsky-Glahn, Vera
author_facet Pawlowsky-Glahn, Vera
Egozcue, Juan José
Olea, Ricardo A.
Pardo-Igúzquiza, Eulogio
author_role author
author2 Egozcue, Juan José
Olea, Ricardo A.
Pardo-Igúzquiza, Eulogio
author2_role author
author
author
dc.contributor.none.fl_str_mv Ministerio de Ciencia e Innovación (Espanya)
dc.subject.none.fl_str_mv Geologia -- Mètodes estadístics
Geology -- Statistical methods
Correlació (Estadística)
Correlation (Statistics)
Geoquímica
Geochemistry
Anàlisi multivariable
Multivariate analysis
topic Geologia -- Mètodes estadístics
Geology -- Statistical methods
Correlació (Estadística)
Correlation (Statistics)
Geoquímica
Geochemistry
Anàlisi multivariable
Multivariate analysis
description Compositional data constitutes a special class of quantitative measurements involving parts of a whole. The sample space has an algebraic-geometric structure different from that of real-valued data. A subcomposition is a subset of all possible parts. When compositional data values include geographical locations, they are also regionalized variables. In the Earth sciences, geochemical analyses are a common form of regionalized compositional data. Ordinarily, there are measurements only at data locations. Geostatistics has proven to be the standard for spatial estimation of regionalized variables but, in general, the compositional character of the geochemical data has been ignored. This paper presents in detail an application of cokriging for the modelling of compositional data using a method that is consistent with the compositional character of the data. The uncertainty is evaluated by a Monte Carlo procedure. The method is illustrated for the contents of arsenic and iron in groundwaters in Bangladesh, which have the peculiarity of being measured in milligrams per litre, units for which the sum of all parts does not add to a constant. Practical results include maps of estimates of the geochemical elements in the original concentration units, as well as measures of uncertainty, such as the probability that the concentration may exceed a given threshold. Results indicate that probabilities of exceedance in previous studies of the same data are too low
publishDate 2015
dc.date.none.fl_str_mv 2015
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10256/13738
http://hdl.handle.net/10256/13738
url http://hdl.handle.net/10256/13738
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/2225-6253
info:eu-repo/semantics/altIdentifier/eissn/2411-9717
info:eu-repo/grantAgreement/MINECO//MTM2012-33236
dc.rights.none.fl_str_mv Attribution 3.0 Spain
http://creativecommons.org/licenses/by/4.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 3.0 Spain
http://creativecommons.org/licenses/by/4.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Southern African Institute of Mining and Metallurgy (SAIMM)
publisher.none.fl_str_mv Southern African Institute of Mining and Metallurgy (SAIMM)
dc.source.none.fl_str_mv The Journal of The Southern African Institute of Mining and Metallurgy, 2015, vol. 115, p.59-72
Articles publicats (D-IMA)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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