Robust consistent estimators for ROC curves with covariates

Autores
Bianco, Ana Maria; Boente Boente, Graciela Lina; González Manteiga, Wenceslao
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The Receiver Operating Characteristic (ROC) curve is a use-ful tool to measure the classification capability of a continuous variable to assess the accuracy of a medical test that distinguishes between two conditions. Sometimes, covariates related to the diagnostic variable may increase the discriminating power of the ROC curve. Due to the lack of stability of classical ROC curves estimators to outliers, we introduce a procedure to obtain robust estimators in presence of covariates. The considered proposal focusses on a semiparametric approach which robustly fits a location-scale regression model to the diagnostic variable and considers robust adaptive empirical estimators of the regression residuals. The uniform consistency of the proposal is derived under mild assumptions. A Monte Carlo study is carried out to compare the performance of the robust proposed estimators with the classical ones both, in clean and contaminated samples. A real data set is also analysed.
Fil: Bianco, Ana Maria. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; Argentina
Fil: Boente Boente, Graciela Lina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: González Manteiga, Wenceslao. Universidad de Santiago de Compostela; España
Materia
COVARIATES
PARAMETRIC REGRESSION
ROBUSTNESS
ROC CURVES
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:11336/202449
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Robust consistent estimators for ROC curves with covariatesBianco, Ana MariaBoente Boente, Graciela LinaGonzález Manteiga, WenceslaoCOVARIATESPARAMETRIC REGRESSIONROBUSTNESSROC CURVEShttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1The Receiver Operating Characteristic (ROC) curve is a use-ful tool to measure the classification capability of a continuous variable to assess the accuracy of a medical test that distinguishes between two conditions. Sometimes, covariates related to the diagnostic variable may increase the discriminating power of the ROC curve. Due to the lack of stability of classical ROC curves estimators to outliers, we introduce a procedure to obtain robust estimators in presence of covariates. The considered proposal focusses on a semiparametric approach which robustly fits a location-scale regression model to the diagnostic variable and considers robust adaptive empirical estimators of the regression residuals. The uniform consistency of the proposal is derived under mild assumptions. A Monte Carlo study is carried out to compare the performance of the robust proposed estimators with the classical ones both, in clean and contaminated samples. A real data set is also analysed.Fil: Bianco, Ana Maria. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; ArgentinaFil: Boente Boente, Graciela Lina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: González Manteiga, Wenceslao. Universidad de Santiago de Compostela; EspañaInstitute of Mathematical Statistics2022-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/202449Bianco, Ana Maria; Boente Boente, Graciela Lina; González Manteiga, Wenceslao; Robust consistent estimators for ROC curves with covariates; Institute of Mathematical Statistics; Electronic Journal of Statistics; 16; 2; 7-2022; 4133-41611935-7524CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://projecteuclid.org/journals/electronic-journal-of-statistics/volume-16/issue-2/Robust-consistent-estimators-for-ROC-curves-with-covariates/10.1214/22-EJS2042.fullinfo:eu-repo/semantics/altIdentifier/doi/10.1214/22-EJS2042info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:17:57Zoai:ri.conicet.gov.ar:11336/202449instacron: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:34982025-09-29 10:17:57.303CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Robust consistent estimators for ROC curves with covariates
title Robust consistent estimators for ROC curves with covariates
spellingShingle Robust consistent estimators for ROC curves with covariates
Bianco, Ana Maria
COVARIATES
PARAMETRIC REGRESSION
ROBUSTNESS
ROC CURVES
title_short Robust consistent estimators for ROC curves with covariates
title_full Robust consistent estimators for ROC curves with covariates
title_fullStr Robust consistent estimators for ROC curves with covariates
title_full_unstemmed Robust consistent estimators for ROC curves with covariates
title_sort Robust consistent estimators for ROC curves with covariates
dc.creator.none.fl_str_mv Bianco, Ana Maria
Boente Boente, Graciela Lina
González Manteiga, Wenceslao
author Bianco, Ana Maria
author_facet Bianco, Ana Maria
Boente Boente, Graciela Lina
González Manteiga, Wenceslao
author_role author
author2 Boente Boente, Graciela Lina
González Manteiga, Wenceslao
author2_role author
author
dc.subject.none.fl_str_mv COVARIATES
PARAMETRIC REGRESSION
ROBUSTNESS
ROC CURVES
topic COVARIATES
PARAMETRIC REGRESSION
ROBUSTNESS
ROC CURVES
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The Receiver Operating Characteristic (ROC) curve is a use-ful tool to measure the classification capability of a continuous variable to assess the accuracy of a medical test that distinguishes between two conditions. Sometimes, covariates related to the diagnostic variable may increase the discriminating power of the ROC curve. Due to the lack of stability of classical ROC curves estimators to outliers, we introduce a procedure to obtain robust estimators in presence of covariates. The considered proposal focusses on a semiparametric approach which robustly fits a location-scale regression model to the diagnostic variable and considers robust adaptive empirical estimators of the regression residuals. The uniform consistency of the proposal is derived under mild assumptions. A Monte Carlo study is carried out to compare the performance of the robust proposed estimators with the classical ones both, in clean and contaminated samples. A real data set is also analysed.
Fil: Bianco, Ana Maria. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; Argentina
Fil: Boente Boente, Graciela Lina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: González Manteiga, Wenceslao. Universidad de Santiago de Compostela; España
description The Receiver Operating Characteristic (ROC) curve is a use-ful tool to measure the classification capability of a continuous variable to assess the accuracy of a medical test that distinguishes between two conditions. Sometimes, covariates related to the diagnostic variable may increase the discriminating power of the ROC curve. Due to the lack of stability of classical ROC curves estimators to outliers, we introduce a procedure to obtain robust estimators in presence of covariates. The considered proposal focusses on a semiparametric approach which robustly fits a location-scale regression model to the diagnostic variable and considers robust adaptive empirical estimators of the regression residuals. The uniform consistency of the proposal is derived under mild assumptions. A Monte Carlo study is carried out to compare the performance of the robust proposed estimators with the classical ones both, in clean and contaminated samples. A real data set is also analysed.
publishDate 2022
dc.date.none.fl_str_mv 2022-07
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/11336/202449
Bianco, Ana Maria; Boente Boente, Graciela Lina; González Manteiga, Wenceslao; Robust consistent estimators for ROC curves with covariates; Institute of Mathematical Statistics; Electronic Journal of Statistics; 16; 2; 7-2022; 4133-4161
1935-7524
CONICET Digital
CONICET
url http://hdl.handle.net/11336/202449
identifier_str_mv Bianco, Ana Maria; Boente Boente, Graciela Lina; González Manteiga, Wenceslao; Robust consistent estimators for ROC curves with covariates; Institute of Mathematical Statistics; Electronic Journal of Statistics; 16; 2; 7-2022; 4133-4161
1935-7524
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://projecteuclid.org/journals/electronic-journal-of-statistics/volume-16/issue-2/Robust-consistent-estimators-for-ROC-curves-with-covariates/10.1214/22-EJS2042.full
info:eu-repo/semantics/altIdentifier/doi/10.1214/22-EJS2042
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 Institute of Mathematical Statistics
publisher.none.fl_str_mv Institute of Mathematical Statistics
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 13.070432

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