Robust estimation for nonparametric generalized regression

This paper focuses on nonparametric regression estimation for the parameters of a discrete or continuous distribution, such as the Poisson or Gamma distributions, when anomalous data are present. The proposal is a natural extension of robust methods developed in the setting of parametric generalized...

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Detalles Bibliográficos
Autores: Bianco, Ana Maria, Boente Boente, Graciela Lina, Sombielle, Susana
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2011
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/14907
Acceso en línea:http://hdl.handle.net/11336/14907
Access Level:acceso abierto
Palabra clave:Asymptotic Properties
Nonparametric Generalized Regression
Robust Estimation
Smoothing Techniques
https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
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spelling Robust estimation for nonparametric generalized regressionBianco, Ana MariaBoente Boente, Graciela LinaSombielle, SusanaAsymptotic PropertiesNonparametric Generalized RegressionRobust EstimationSmoothing Techniqueshttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1This paper focuses on nonparametric regression estimation for the parameters of a discrete or continuous distribution, such as the Poisson or Gamma distributions, when anomalous data are present. The proposal is a natural extension of robust methods developed in the setting of parametric generalized linear models. Robust estimators bounding either large values of the deviance or of the Pearson residuals are introduced and their asymptotic behaviour is derived. Through a Monte Carlo study, for the Poisson and Gamma distributions, the finite properties of the proposed procedures are investigated and their performance is compared with that of the classical ones. A resistant cross-validation method to choose the smoothing parameter is also considered.Fil: Bianco, Ana Maria. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: 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: Sombielle, Susana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Universidad Tecnologica Nacional; ArgentinaElsevier2011-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/14907Bianco, Ana Maria; Boente Boente, Graciela Lina; Sombielle, Susana; Robust estimation for nonparametric generalized regression; Elsevier; Statistics & Probability Letters; 81; 12; 12-2011; 1986-19940167-7152enginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0167715211002719info:eu-repo/semantics/altIdentifier/doi/10.1016/j.spl.2011.08.007info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2024-05-08T13:44:23Zoai:ri.conicet.gov.ar:11336/14907instacron: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:34982024-05-08 13:44:23.511CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Robust estimation for nonparametric generalized regression
title Robust estimation for nonparametric generalized regression
spellingShingle Robust estimation for nonparametric generalized regression
Bianco, Ana Maria
Asymptotic Properties
Nonparametric Generalized Regression
Robust Estimation
Smoothing Techniques
https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
title_short Robust estimation for nonparametric generalized regression
title_full Robust estimation for nonparametric generalized regression
title_fullStr Robust estimation for nonparametric generalized regression
title_full_unstemmed Robust estimation for nonparametric generalized regression
title_sort Robust estimation for nonparametric generalized regression
dc.creator.none.fl_str_mv Bianco, Ana Maria
Boente Boente, Graciela Lina
Sombielle, Susana
author Bianco, Ana Maria
author_facet Bianco, Ana Maria
Boente Boente, Graciela Lina
Sombielle, Susana
author_role author
author2 Boente Boente, Graciela Lina
Sombielle, Susana
author2_role author
author
dc.subject.none.fl_str_mv Asymptotic Properties
Nonparametric Generalized Regression
Robust Estimation
Smoothing Techniques
https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
topic Asymptotic Properties
Nonparametric Generalized Regression
Robust Estimation
Smoothing Techniques
https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
description This paper focuses on nonparametric regression estimation for the parameters of a discrete or continuous distribution, such as the Poisson or Gamma distributions, when anomalous data are present. The proposal is a natural extension of robust methods developed in the setting of parametric generalized linear models. Robust estimators bounding either large values of the deviance or of the Pearson residuals are introduced and their asymptotic behaviour is derived. Through a Monte Carlo study, for the Poisson and Gamma distributions, the finite properties of the proposed procedures are investigated and their performance is compared with that of the classical ones. A resistant cross-validation method to choose the smoothing parameter is also considered.
publishDate 2011
dc.date.none.fl_str_mv 2011-12
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/11336/14907
Bianco, Ana Maria; Boente Boente, Graciela Lina; Sombielle, Susana; Robust estimation for nonparametric generalized regression; Elsevier; Statistics & Probability Letters; 81; 12; 12-2011; 1986-1994
0167-7152
url http://hdl.handle.net/11336/14907
identifier_str_mv Bianco, Ana Maria; Boente Boente, Graciela Lina; Sombielle, Susana; Robust estimation for nonparametric generalized regression; Elsevier; Statistics & Probability Letters; 81; 12; 12-2011; 1986-1994
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/S0167715211002719
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.spl.2011.08.007
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
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
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 15,81155

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