A New Way for Ranking Functional Data With Applications in Diagnostic Test

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UDC.coleccionInvestigaciónes_ES
UDC.departamentoMatemáticases_ES
UDC.endPage154es_ES
UDC.grupoInvModelización, Optimización e Inferencia Estatística (MODES)es_ES
UDC.journalTitleComputational Statisticses_ES
UDC.startPage127es_ES
UDC.volume36 (2021)es_ES
dc.contributor.authorEstévez-Pérez, G.
dc.contributor.authorVieu, Philippe
dc.date.accessioned2024-11-12T20:17:57Z
dc.date.available2024-11-12T20:17:57Z
dc.date.issued2020-07-17
dc.descriptionThis is an accepted version of the published document. This version of the article has been accepted for publication, after peer review (when applicable), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s00180-020-01020-zes_ES
dc.description.abstract[Abstract] This is a two faces paper. Firstly, it investigates diagnostic tests in situations when the observed variables are functional, that is, diagnostic tests that use functional variables as biomarkers. A procedure based on functional version of ROC analysis is proposed, the main question being linked with a suitable way for ranking the sample of functional data. The second facet of this paper is to present a general new way for ordering functional data in a self-contained way allowing for a wide scope of applications overpassing the former diagnostic test problem. Finite sample analysis highlight how this ranking procedure behaves for diagnostic test.es_ES
dc.description.sponsorshipThis research has been supported by MINECO (Grant MTM2014-52876-R), by Xunta de Galicia (Centro Singular de Investigación de Galicia ED431G/01 and Grupos de Referencia Competitiva ED431C2016-015), all of them through the ERDF. The authors would like to thank the Associate Editor and the two anonymous referees for their constructive and helpful comments, which have greatly improved the paperes_ES
dc.description.sponsorshipXunta de Galicia; ED431G/01es_ES
dc.description.sponsorshipXunta de Galicia; ED431C2016-015es_ES
dc.identifier.citationEstévez-Pérez, G., Vieu, P. A new way for ranking functional data with applications in diagnostic test. Comput Stat 36, 127–154 (2021). https://doi.org/10.1007/s00180-020-01020-zes_ES
dc.identifier.doi10.1007/s00180-020-01020-z
dc.identifier.issn1613-9658
dc.identifier.urihttp://hdl.handle.net/2183/40089
dc.language.isoenges_ES
dc.publisherSpringer Naturees_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2014-52876-R/ES/INFERENCIA ESTADISTICA COMPLEJA Y DE ALTA DIMENSION: EN GENOMICA, NEUROCIENCIA, ONCOLOGIA, MATERIALES COMPLEJOS, MALHERBOLOGIA, MEDIO AMBIENTE, ENERGIA Y APLICACIONES INDUSTRIes_ES
dc.relation.urihttps://doi.org/10.1007/s00180-020-01020-zes_ES
dc.rights© 2020, Springer-Verlag GmbH Germany, part of Springer Nature. Subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms)es_ES
dc.rights.accessRightsopen accesses_ES
dc.subjectDiagnostic testes_ES
dc.subjectOrderinges_ES
dc.subjectFunctional biomarkerses_ES
dc.subjectROC curveses_ES
dc.titleA New Way for Ranking Functional Data With Applications in Diagnostic Testes_ES
dc.typejournal articlees_ES
dspace.entity.typePublication
relation.isAuthorOfPublication6542ab1a-3551-4940-91a4-e775a166a241
relation.isAuthorOfPublication.latestForDiscovery6542ab1a-3551-4940-91a4-e775a166a241

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