Robust inference in partially linear models with missing responses
- Autores
- Bianco, Ana Maria; Boente Boente, Graciela Lina; González Manteiga, Wenceslao; Pérez González, Ana
- Año de publicación
- 2014
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- We consider robust testing on the regression parameter of a partially linear regression model, where missing responses are allowed. We derive the asymptotic behavior of the proposed test statistic under the null and contiguous alternatives. A numerical study is performed.
Fil: Bianco, Ana Maria. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Boente Boente, Graciela Lina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; Argentina
Fil: González Manteiga, Wenceslao. Universidad de Santiago de Compostela; España
Fil: Pérez González, Ana. Universidad de Vigo; España - Materia
-
Kernel Weights
Hypothesis Testing
M-Location Functionals
Missing at Random
Partly Linear Models
Robust Estimation - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/20968
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Robust inference in partially linear models with missing responsesBianco, Ana MariaBoente Boente, Graciela LinaGonzález Manteiga, WenceslaoPérez González, AnaKernel WeightsHypothesis TestingM-Location FunctionalsMissing at RandomPartly Linear ModelsRobust Estimationhttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1We consider robust testing on the regression parameter of a partially linear regression model, where missing responses are allowed. We derive the asymptotic behavior of the proposed test statistic under the null and contiguous alternatives. A numerical study is performed.Fil: Bianco, Ana Maria. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Boente Boente, Graciela Lina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; ArgentinaFil: González Manteiga, Wenceslao. Universidad de Santiago de Compostela; EspañaFil: Pérez González, Ana. Universidad de Vigo; EspañaElsevier Science2014-11info: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/11336/20968Bianco, Ana Maria; Boente Boente, Graciela Lina; González Manteiga, Wenceslao; Pérez González, Ana; Robust inference in partially linear models with missing responses; Elsevier Science; Statistics & Probability Letters; 97; 11-2014; 88-980167-7152CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.spl.2014.11.004info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0167715214003733info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:05:19Zoai:ri.conicet.gov.ar:11336/20968instacron: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:34982025-09-03 10:05:20.155CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Robust inference in partially linear models with missing responses |
title |
Robust inference in partially linear models with missing responses |
spellingShingle |
Robust inference in partially linear models with missing responses Bianco, Ana Maria Kernel Weights Hypothesis Testing M-Location Functionals Missing at Random Partly Linear Models Robust Estimation |
title_short |
Robust inference in partially linear models with missing responses |
title_full |
Robust inference in partially linear models with missing responses |
title_fullStr |
Robust inference in partially linear models with missing responses |
title_full_unstemmed |
Robust inference in partially linear models with missing responses |
title_sort |
Robust inference in partially linear models with missing responses |
dc.creator.none.fl_str_mv |
Bianco, Ana Maria Boente Boente, Graciela Lina González Manteiga, Wenceslao Pérez González, Ana |
author |
Bianco, Ana Maria |
author_facet |
Bianco, Ana Maria Boente Boente, Graciela Lina González Manteiga, Wenceslao Pérez González, Ana |
author_role |
author |
author2 |
Boente Boente, Graciela Lina González Manteiga, Wenceslao Pérez González, Ana |
author2_role |
author author author |
dc.subject.none.fl_str_mv |
Kernel Weights Hypothesis Testing M-Location Functionals Missing at Random Partly Linear Models Robust Estimation |
topic |
Kernel Weights Hypothesis Testing M-Location Functionals Missing at Random Partly Linear Models Robust Estimation |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.1 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
We consider robust testing on the regression parameter of a partially linear regression model, where missing responses are allowed. We derive the asymptotic behavior of the proposed test statistic under the null and contiguous alternatives. A numerical study is performed. Fil: Bianco, Ana Maria. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Boente Boente, Graciela Lina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; Argentina Fil: González Manteiga, Wenceslao. Universidad de Santiago de Compostela; España Fil: Pérez González, Ana. Universidad de Vigo; España |
description |
We consider robust testing on the regression parameter of a partially linear regression model, where missing responses are allowed. We derive the asymptotic behavior of the proposed test statistic under the null and contiguous alternatives. A numerical study is performed. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-11 |
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/11336/20968 Bianco, Ana Maria; Boente Boente, Graciela Lina; González Manteiga, Wenceslao; Pérez González, Ana; Robust inference in partially linear models with missing responses; Elsevier Science; Statistics & Probability Letters; 97; 11-2014; 88-98 0167-7152 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/20968 |
identifier_str_mv |
Bianco, Ana Maria; Boente Boente, Graciela Lina; González Manteiga, Wenceslao; Pérez González, Ana; Robust inference in partially linear models with missing responses; Elsevier Science; Statistics & Probability Letters; 97; 11-2014; 88-98 0167-7152 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.spl.2014.11.004 info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0167715214003733 |
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 application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier Science |
publisher.none.fl_str_mv |
Elsevier Science |
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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1842269905926225920 |
score |
13.13397 |