Testing in generalized partly linear models: A robust approach

Autores
Boente Boente, Graciela Lina; Cao, Ricardo; Gonzalez Manteiga, Wenceslao; Rodriguez, Daniela Andrea
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this paper, we introduce a family of robust statistics which allow to decide between a parametric model and a semiparametric one. More precisely, under a generalized partially linear model, i.e., when the observations satisfy View the MathML source with View the MathML source and H a known link function, we want to test H0:η(t)=α+γt against H1:η is a nonlinear smooth function. A general approach which includes robust estimators based on a robustified deviance or a robustified quasi-likelihood is considered. The asymptotic behavior of the test statistic under the null hypothesis is obtained.
Fil: Boente Boente, Graciela Lina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; Argentina
Fil: Cao, Ricardo. Universidad da Coruña; España
Fil: Gonzalez Manteiga, Wenceslao. Universidad de Santiago de Compostela; España
Fil: Rodriguez, Daniela Andrea. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; Argentina
Materia
Generalized Partially Linear Models
Kernel Weights
Rate of Convergence
Robust Testing
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/14885
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Testing in generalized partly linear models: A robust approachBoente Boente, Graciela LinaCao, RicardoGonzalez Manteiga, WenceslaoRodriguez, Daniela AndreaGeneralized Partially Linear ModelsKernel WeightsRate of ConvergenceRobust Testinghttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1In this paper, we introduce a family of robust statistics which allow to decide between a parametric model and a semiparametric one. More precisely, under a generalized partially linear model, i.e., when the observations satisfy View the MathML source with View the MathML source and H a known link function, we want to test H0:η(t)=α+γt against H1:η is a nonlinear smooth function. A general approach which includes robust estimators based on a robustified deviance or a robustified quasi-likelihood is considered. The asymptotic behavior of the test statistic under the null hypothesis is obtained.Fil: Boente Boente, Graciela Lina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; ArgentinaFil: Cao, Ricardo. Universidad da Coruña; EspañaFil: Gonzalez Manteiga, Wenceslao. Universidad de Santiago de Compostela; EspañaFil: Rodriguez, Daniela Andrea. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; ArgentinaElsevier2013-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/14885Boente Boente, Graciela Lina; Cao, Ricardo; Gonzalez Manteiga, Wenceslao; Rodriguez, Daniela Andrea; Testing in generalized partly linear models: A robust approach; Elsevier; Statistics & Probability Letters; 83; 1; 1-2013; 203-2120167-7152enginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0167715212003367info:eu-repo/semantics/altIdentifier/doi/10.1016/j.spl.2012.08.031info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:47:19Zoai:ri.conicet.gov.ar:11336/14885instacron: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 09:47:19.74CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Testing in generalized partly linear models: A robust approach
title Testing in generalized partly linear models: A robust approach
spellingShingle Testing in generalized partly linear models: A robust approach
Boente Boente, Graciela Lina
Generalized Partially Linear Models
Kernel Weights
Rate of Convergence
Robust Testing
title_short Testing in generalized partly linear models: A robust approach
title_full Testing in generalized partly linear models: A robust approach
title_fullStr Testing in generalized partly linear models: A robust approach
title_full_unstemmed Testing in generalized partly linear models: A robust approach
title_sort Testing in generalized partly linear models: A robust approach
dc.creator.none.fl_str_mv Boente Boente, Graciela Lina
Cao, Ricardo
Gonzalez Manteiga, Wenceslao
Rodriguez, Daniela Andrea
author Boente Boente, Graciela Lina
author_facet Boente Boente, Graciela Lina
Cao, Ricardo
Gonzalez Manteiga, Wenceslao
Rodriguez, Daniela Andrea
author_role author
author2 Cao, Ricardo
Gonzalez Manteiga, Wenceslao
Rodriguez, Daniela Andrea
author2_role author
author
author
dc.subject.none.fl_str_mv Generalized Partially Linear Models
Kernel Weights
Rate of Convergence
Robust Testing
topic Generalized Partially Linear Models
Kernel Weights
Rate of Convergence
Robust Testing
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In this paper, we introduce a family of robust statistics which allow to decide between a parametric model and a semiparametric one. More precisely, under a generalized partially linear model, i.e., when the observations satisfy View the MathML source with View the MathML source and H a known link function, we want to test H0:η(t)=α+γt against H1:η is a nonlinear smooth function. A general approach which includes robust estimators based on a robustified deviance or a robustified quasi-likelihood is considered. The asymptotic behavior of the test statistic under the null hypothesis is obtained.
Fil: Boente Boente, Graciela Lina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; Argentina
Fil: Cao, Ricardo. Universidad da Coruña; España
Fil: Gonzalez Manteiga, Wenceslao. Universidad de Santiago de Compostela; España
Fil: Rodriguez, Daniela Andrea. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; Argentina
description In this paper, we introduce a family of robust statistics which allow to decide between a parametric model and a semiparametric one. More precisely, under a generalized partially linear model, i.e., when the observations satisfy View the MathML source with View the MathML source and H a known link function, we want to test H0:η(t)=α+γt against H1:η is a nonlinear smooth function. A general approach which includes robust estimators based on a robustified deviance or a robustified quasi-likelihood is considered. The asymptotic behavior of the test statistic under the null hypothesis is obtained.
publishDate 2013
dc.date.none.fl_str_mv 2013-01
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/11336/14885
Boente Boente, Graciela Lina; Cao, Ricardo; Gonzalez Manteiga, Wenceslao; Rodriguez, Daniela Andrea; Testing in generalized partly linear models: A robust approach; Elsevier; Statistics & Probability Letters; 83; 1; 1-2013; 203-212
0167-7152
url http://hdl.handle.net/11336/14885
identifier_str_mv Boente Boente, Graciela Lina; Cao, Ricardo; Gonzalez Manteiga, Wenceslao; Rodriguez, Daniela Andrea; Testing in generalized partly linear models: A robust approach; Elsevier; Statistics & Probability Letters; 83; 1; 1-2013; 203-212
0167-7152
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0167715212003367
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.spl.2012.08.031
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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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