Bandwidth choice for robust nonparametric scale function estimation

Autores
Boente Boente, Graciela Lina; Ruiz, Marcelo; Zamar, Rubén
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We introduce and compare several robust procedures for bandwidth selection when estimating the variance function. These bandwidth selectors are to be used in combination with the robust scale estimates introduced by Boente et al. (2010a). We consider two different robust cross--validation strategies combined with two ways for measuring the cross--validation prediction error. The different proposals are compared with non robust alternatives using Monte Carlo simulation. We also derive some asymptotic results to investigate the large sample performance of the corresponding robust data--driven scale estimators.
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"; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Ruiz, Marcelo. Universidad Nacional de Rio Cuarto; Argentina
Fil: Zamar, Rubén. University Of British Columbia; Canadá
Materia
Cross-Validation
Data-Driven Bandwidth
Heteroscedasticity
Local M-Estimators
Nonparametric Regression
Robust Estimation
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:11336/14886
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/14886
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Bandwidth choice for robust nonparametric scale function estimationBoente Boente, Graciela LinaRuiz, MarceloZamar, RubénCross-ValidationData-Driven BandwidthHeteroscedasticityLocal M-EstimatorsNonparametric RegressionRobust Estimationhttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1We introduce and compare several robust procedures for bandwidth selection when estimating the variance function. These bandwidth selectors are to be used in combination with the robust scale estimates introduced by Boente et al. (2010a). We consider two different robust cross--validation strategies combined with two ways for measuring the cross--validation prediction error. The different proposals are compared with non robust alternatives using Monte Carlo simulation. We also derive some asymptotic results to investigate the large sample performance of the corresponding robust data--driven scale estimators.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"; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Ruiz, Marcelo. Universidad Nacional de Rio Cuarto; ArgentinaFil: Zamar, Rubén. University Of British Columbia; CanadáElsevier2012-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/14886Boente Boente, Graciela Lina; Ruiz, Marcelo; Zamar, Rubén; Bandwidth choice for robust nonparametric scale function estimation; Elsevier; Computational Statistics And Data Analysis; 56; 6; 6-2012; 1594-16080167-9473enginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0167947311003598info:eu-repo/semantics/altIdentifier/doi/10.1016/j.csda.2011.10.002info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:54:39Zoai:ri.conicet.gov.ar:11336/14886instacron: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 09:54:39.442CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Bandwidth choice for robust nonparametric scale function estimation
title Bandwidth choice for robust nonparametric scale function estimation
spellingShingle Bandwidth choice for robust nonparametric scale function estimation
Boente Boente, Graciela Lina
Cross-Validation
Data-Driven Bandwidth
Heteroscedasticity
Local M-Estimators
Nonparametric Regression
Robust Estimation
title_short Bandwidth choice for robust nonparametric scale function estimation
title_full Bandwidth choice for robust nonparametric scale function estimation
title_fullStr Bandwidth choice for robust nonparametric scale function estimation
title_full_unstemmed Bandwidth choice for robust nonparametric scale function estimation
title_sort Bandwidth choice for robust nonparametric scale function estimation
dc.creator.none.fl_str_mv Boente Boente, Graciela Lina
Ruiz, Marcelo
Zamar, Rubén
author Boente Boente, Graciela Lina
author_facet Boente Boente, Graciela Lina
Ruiz, Marcelo
Zamar, Rubén
author_role author
author2 Ruiz, Marcelo
Zamar, Rubén
author2_role author
author
dc.subject.none.fl_str_mv Cross-Validation
Data-Driven Bandwidth
Heteroscedasticity
Local M-Estimators
Nonparametric Regression
Robust Estimation
topic Cross-Validation
Data-Driven Bandwidth
Heteroscedasticity
Local M-Estimators
Nonparametric Regression
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 introduce and compare several robust procedures for bandwidth selection when estimating the variance function. These bandwidth selectors are to be used in combination with the robust scale estimates introduced by Boente et al. (2010a). We consider two different robust cross--validation strategies combined with two ways for measuring the cross--validation prediction error. The different proposals are compared with non robust alternatives using Monte Carlo simulation. We also derive some asymptotic results to investigate the large sample performance of the corresponding robust data--driven scale estimators.
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"; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Ruiz, Marcelo. Universidad Nacional de Rio Cuarto; Argentina
Fil: Zamar, Rubén. University Of British Columbia; Canadá
description We introduce and compare several robust procedures for bandwidth selection when estimating the variance function. These bandwidth selectors are to be used in combination with the robust scale estimates introduced by Boente et al. (2010a). We consider two different robust cross--validation strategies combined with two ways for measuring the cross--validation prediction error. The different proposals are compared with non robust alternatives using Monte Carlo simulation. We also derive some asymptotic results to investigate the large sample performance of the corresponding robust data--driven scale estimators.
publishDate 2012
dc.date.none.fl_str_mv 2012-06
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/11336/14886
Boente Boente, Graciela Lina; Ruiz, Marcelo; Zamar, Rubén; Bandwidth choice for robust nonparametric scale function estimation; Elsevier; Computational Statistics And Data Analysis; 56; 6; 6-2012; 1594-1608
0167-9473
url http://hdl.handle.net/11336/14886
identifier_str_mv Boente Boente, Graciela Lina; Ruiz, Marcelo; Zamar, Rubén; Bandwidth choice for robust nonparametric scale function estimation; Elsevier; Computational Statistics And Data Analysis; 56; 6; 6-2012; 1594-1608
0167-9473
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/S0167947311003598
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.csda.2011.10.002
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
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
_version_ 1842269298796527616
score 13.13397

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