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dc.contributor.authorOviedo de la Fuente, Manuel
dc.contributor.authorOrdóñez, Celestino
dc.contributor.authorRoca Pardiñas, Javier
dc.date.accessioned2020-11-10T11:09:24Z
dc.date.available2020-11-10T11:09:24Z
dc.date.issued2020
dc.identifier.citationOviedo-de La Fuente, M.; Ordóñez, C.; Roca-Pardiñas, J. Functional Location-Scale Model to Forecast Bivariate Pollution Episodes. Mathematics 2020, 8, 941
dc.identifier.urihttp://hdl.handle.net/10347/23639
dc.description.abstractPredicting anomalous emission of pollutants into the atmosphere well in advance is crucial for industries emitting such elements, since it allows them to take corrective measures aimed to avoid such emissions and their consequences. In this work, we propose a functional location-scale model to predict in advance pollution episodes where two pollutants are involved. Functional generalized additive models (FGAMs) are used to estimate the means and variances of the model, as well as the correlation between both pollutants. The method not only forecasts the concentrations of both pollutants, it also estimates an uncertainty region where the concentrations of both pollutants should be located, given a specific level of uncertainty. The performance of the model was evaluated using real data of SO 2 and NO x emissions from a coal-fired power station, obtaining good results
dc.description.sponsorshipThe authors acknowledge financial support from: (1) UO-Proyecto Uni-Ovi (PAPI-18-GR-2014-0014), (2) Project MTM2016-76969-P from Ministerio de Economía y Competitividad—Agencia Estatal de Investigación and European Regional Development Fund (ERDF) and IAP network StUDyS from Belgian Science Policy, (3) Nuevos avances metodológicos y computacionales en estadística no-paramétrica y semiparamétrica—Ministerio de Ciencia e Investigación (MTM2017-89422-P)
dc.language.isoeng
dc.publisherMDPI
dc.rights© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)
dc.rightsAtribución 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectPollution episodes
dc.subjectFunctional data
dc.subjectBivariate analysis
dc.subjectUncertainty region
dc.subjectGeneralized additive models
dc.titleFunctional Location-Scale Model to Forecast Bivariate Pollution Episodes
dc.typejournal article
dc.identifier.doi10.3390/math8060941
dc.relation.publisherversionhttps://doi.org/10.3390/math8060941
dc.type.hasVersionVoR
dc.identifier.essn2227-7390
dc.rights.accessRightsopen access
dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Estatística, Análise Matemática e Optimización
dc.description.peerreviewedSI
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2016-76969-P/ES


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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)
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 © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)





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