Continuity and differentiability of regression M functionals
- Autores
- Fasano, Maria Victoria; Maronna, Ricardo Antonio; Sued, Raquel Mariela; Yohai, Victor Jaime
- Año de publicación
- 2012
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- This paper deals with the Fisher-consistency, weak continuity and differentiability of estimating functionals corresponding to a class of both linear and nonlinear regression high breakdown M estimates, which includes S and MM estimates. A restricted type of differentiability, called weak differentiability, is defined, which suffices to prove the asymptotic normality of estimates based on the functionals. This approach allows to prove the consistency, asymptotic normality and qualitative robustness of M estimates under more general conditions than those required in standard approaches. In particular, we prove that regression MMestimates are asymptotically normal when the observations are φ-mixing.
Fil: Fasano, Maria Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Matemáticas; Argentina
Fil: Maronna, Ricardo Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Matemáticas; Argentina
Fil: Sued, Raquel Mariela. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina
Fil: Yohai, Victor Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; Argentina - Materia
-
ASYMPTOTIC NORMALITY
CONSISTENCY
MM ESTIMATES
NONLINEAR REGRESSION
S ESTIMATES - 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:11336/69605
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Continuity and differentiability of regression M functionalsFasano, Maria VictoriaMaronna, Ricardo AntonioSued, Raquel MarielaYohai, Victor JaimeASYMPTOTIC NORMALITYCONSISTENCYMM ESTIMATESNONLINEAR REGRESSIONS ESTIMATEShttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1This paper deals with the Fisher-consistency, weak continuity and differentiability of estimating functionals corresponding to a class of both linear and nonlinear regression high breakdown M estimates, which includes S and MM estimates. A restricted type of differentiability, called weak differentiability, is defined, which suffices to prove the asymptotic normality of estimates based on the functionals. This approach allows to prove the consistency, asymptotic normality and qualitative robustness of M estimates under more general conditions than those required in standard approaches. In particular, we prove that regression MMestimates are asymptotically normal when the observations are φ-mixing.Fil: Fasano, Maria Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Matemáticas; ArgentinaFil: Maronna, Ricardo Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Matemáticas; ArgentinaFil: Sued, Raquel Mariela. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; ArgentinaFil: Yohai, Victor Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; ArgentinaInstitute of Mathematical Statistics2012-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/69605Fasano, Maria Victoria; Maronna, Ricardo Antonio; Sued, Raquel Mariela; Yohai, Victor Jaime; Continuity and differentiability of regression M functionals; Institute of Mathematical Statistics; Bernoulli - Mathematical Statistics And Probability; 18; 4; 11-2012; 1284-13091350-7265CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.3150/11-BEJ368info:eu-repo/semantics/altIdentifier/url/https://arxiv.org/pdf/1004.4314.pdfinfo:eu-repo/semantics/altIdentifier/url/https://projecteuclid.org/euclid.bj/1352727811info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:34:53Zoai:ri.conicet.gov.ar:11336/69605instacron: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 09:34:54.006CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Continuity and differentiability of regression M functionals |
title |
Continuity and differentiability of regression M functionals |
spellingShingle |
Continuity and differentiability of regression M functionals Fasano, Maria Victoria ASYMPTOTIC NORMALITY CONSISTENCY MM ESTIMATES NONLINEAR REGRESSION S ESTIMATES |
title_short |
Continuity and differentiability of regression M functionals |
title_full |
Continuity and differentiability of regression M functionals |
title_fullStr |
Continuity and differentiability of regression M functionals |
title_full_unstemmed |
Continuity and differentiability of regression M functionals |
title_sort |
Continuity and differentiability of regression M functionals |
dc.creator.none.fl_str_mv |
Fasano, Maria Victoria Maronna, Ricardo Antonio Sued, Raquel Mariela Yohai, Victor Jaime |
author |
Fasano, Maria Victoria |
author_facet |
Fasano, Maria Victoria Maronna, Ricardo Antonio Sued, Raquel Mariela Yohai, Victor Jaime |
author_role |
author |
author2 |
Maronna, Ricardo Antonio Sued, Raquel Mariela Yohai, Victor Jaime |
author2_role |
author author author |
dc.subject.none.fl_str_mv |
ASYMPTOTIC NORMALITY CONSISTENCY MM ESTIMATES NONLINEAR REGRESSION S ESTIMATES |
topic |
ASYMPTOTIC NORMALITY CONSISTENCY MM ESTIMATES NONLINEAR REGRESSION S ESTIMATES |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.1 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
This paper deals with the Fisher-consistency, weak continuity and differentiability of estimating functionals corresponding to a class of both linear and nonlinear regression high breakdown M estimates, which includes S and MM estimates. A restricted type of differentiability, called weak differentiability, is defined, which suffices to prove the asymptotic normality of estimates based on the functionals. This approach allows to prove the consistency, asymptotic normality and qualitative robustness of M estimates under more general conditions than those required in standard approaches. In particular, we prove that regression MMestimates are asymptotically normal when the observations are φ-mixing. Fil: Fasano, Maria Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Matemáticas; Argentina Fil: Maronna, Ricardo Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Matemáticas; Argentina Fil: Sued, Raquel Mariela. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina Fil: Yohai, Victor Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; Argentina |
description |
This paper deals with the Fisher-consistency, weak continuity and differentiability of estimating functionals corresponding to a class of both linear and nonlinear regression high breakdown M estimates, which includes S and MM estimates. A restricted type of differentiability, called weak differentiability, is defined, which suffices to prove the asymptotic normality of estimates based on the functionals. This approach allows to prove the consistency, asymptotic normality and qualitative robustness of M estimates under more general conditions than those required in standard approaches. In particular, we prove that regression MMestimates are asymptotically normal when the observations are φ-mixing. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-11 |
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/11336/69605 Fasano, Maria Victoria; Maronna, Ricardo Antonio; Sued, Raquel Mariela; Yohai, Victor Jaime; Continuity and differentiability of regression M functionals; Institute of Mathematical Statistics; Bernoulli - Mathematical Statistics And Probability; 18; 4; 11-2012; 1284-1309 1350-7265 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/69605 |
identifier_str_mv |
Fasano, Maria Victoria; Maronna, Ricardo Antonio; Sued, Raquel Mariela; Yohai, Victor Jaime; Continuity and differentiability of regression M functionals; Institute of Mathematical Statistics; Bernoulli - Mathematical Statistics And Probability; 18; 4; 11-2012; 1284-1309 1350-7265 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.3150/11-BEJ368 info:eu-repo/semantics/altIdentifier/url/https://arxiv.org/pdf/1004.4314.pdf info:eu-repo/semantics/altIdentifier/url/https://projecteuclid.org/euclid.bj/1352727811 |
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 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 |
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CONICET Digital (CONICET) |
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CONICET Digital (CONICET) |
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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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