Local influence in compound-poisson models: perturbing the mean-variance relation

Autores
Ricci, Lila; Alegre, Patricia
Año de publicación
2012
Idioma
español castellano
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Local influence is a useful tool to detect abnormalities in regression models, Cook proposed this method in 1986 for classical regression models and, since then, numerous extensions have been developed. The aim of this paper is to derive methods to asses local influence under various perturbation schemes, for compound-Poisson regression models. These models can be applied to continuous data with positive probability in zero, and they are characterized by the variance function that defines the mean-variance relationship. Formulas are obtained to apply local influence methods for different perturbations and it is of particular interest the perturbation of the parameter that defines the mean-variance relation. These schemes are applied to perturbed data generated by simulations and the sensibility of the method is compared for different values of the parameters. Finally, a real data set about home expenditures is analyzed and local influence graphics are obtained to detect influential points.
Fil: Ricci, Lila. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales; Argentina.
Fil: Alegre, Patricia. Universidad Nacional de Mar del Plata. Facultad de Ciencias Económicas y Sociales; Argentina.
Fuente
Journal of Statistics: Advances in Theory and Applications, 18(1), 37-56. ISSN 0975-1262
Materia
Distribución de Poisson
Modelos de Probabilidad
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
Nülan (UNMDP-FCEyS)
Institución
Universidad Nacional de Mar del Plata. Facultad de Ciencias Económicas y Sociales
OAI Identificador
oai:nulan.mdp.edu.ar:1805
Acceder
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oai_identifier_str oai:nulan.mdp.edu.ar:1805
network_acronym_str NULAN
repository_id_str 1845
network_name_str Nülan (UNMDP-FCEyS)
spelling Local influence in compound-poisson models: perturbing the mean-variance relationRicci, LilaAlegre, PatriciaDistribución de PoissonModelos de ProbabilidadLocal influence is a useful tool to detect abnormalities in regression models, Cook proposed this method in 1986 for classical regression models and, since then, numerous extensions have been developed. The aim of this paper is to derive methods to asses local influence under various perturbation schemes, for compound-Poisson regression models. These models can be applied to continuous data with positive probability in zero, and they are characterized by the variance function that defines the mean-variance relationship. Formulas are obtained to apply local influence methods for different perturbations and it is of particular interest the perturbation of the parameter that defines the mean-variance relation. These schemes are applied to perturbed data generated by simulations and the sensibility of the method is compared for different values of the parameters. Finally, a real data set about home expenditures is analyzed and local influence graphics are obtained to detect influential points.Fil: Ricci, Lila. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Alegre, Patricia. Universidad Nacional de Mar del Plata. Facultad de Ciencias Económicas y Sociales; Argentina.Scientific Advances Publishers2012-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://nulan.mdp.edu.ar/id/eprint/1805/https://nulan.mdp.edu.ar/id/eprint/1805/1/ricci.alegre.2012.pdf Journal of Statistics: Advances in Theory and Applications, 18(1), 37-56. ISSN 0975-1262 reponame:Nülan (UNMDP-FCEyS)instname:Universidad Nacional de Mar del Plata. Facultad de Ciencias Económicas y Socialesspainfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/2.5/ar/2025-09-11T10:19:07Zoai:nulan.mdp.edu.ar:1805instacron:UNMDP-FCEySInstitucionalhttp://nulan.mdp.edu.ar/Universidad públicaNo correspondehttp://nulan.mdp.edu.ar/cgi/oai2cendocu@mdp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:18452025-09-11 10:19:07.717Nülan (UNMDP-FCEyS) - Universidad Nacional de Mar del Plata. Facultad de Ciencias Económicas y Socialesfalse
dc.title.none.fl_str_mv Local influence in compound-poisson models: perturbing the mean-variance relation
title Local influence in compound-poisson models: perturbing the mean-variance relation
spellingShingle Local influence in compound-poisson models: perturbing the mean-variance relation
Ricci, Lila
Distribución de Poisson
Modelos de Probabilidad
title_short Local influence in compound-poisson models: perturbing the mean-variance relation
title_full Local influence in compound-poisson models: perturbing the mean-variance relation
title_fullStr Local influence in compound-poisson models: perturbing the mean-variance relation
title_full_unstemmed Local influence in compound-poisson models: perturbing the mean-variance relation
title_sort Local influence in compound-poisson models: perturbing the mean-variance relation
dc.creator.none.fl_str_mv Ricci, Lila
Alegre, Patricia
author Ricci, Lila
author_facet Ricci, Lila
Alegre, Patricia
author_role author
author2 Alegre, Patricia
author2_role author
dc.subject.none.fl_str_mv Distribución de Poisson
Modelos de Probabilidad
topic Distribución de Poisson
Modelos de Probabilidad
dc.description.none.fl_txt_mv Local influence is a useful tool to detect abnormalities in regression models, Cook proposed this method in 1986 for classical regression models and, since then, numerous extensions have been developed. The aim of this paper is to derive methods to asses local influence under various perturbation schemes, for compound-Poisson regression models. These models can be applied to continuous data with positive probability in zero, and they are characterized by the variance function that defines the mean-variance relationship. Formulas are obtained to apply local influence methods for different perturbations and it is of particular interest the perturbation of the parameter that defines the mean-variance relation. These schemes are applied to perturbed data generated by simulations and the sensibility of the method is compared for different values of the parameters. Finally, a real data set about home expenditures is analyzed and local influence graphics are obtained to detect influential points.
Fil: Ricci, Lila. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales; Argentina.
Fil: Alegre, Patricia. Universidad Nacional de Mar del Plata. Facultad de Ciencias Económicas y Sociales; Argentina.
description Local influence is a useful tool to detect abnormalities in regression models, Cook proposed this method in 1986 for classical regression models and, since then, numerous extensions have been developed. The aim of this paper is to derive methods to asses local influence under various perturbation schemes, for compound-Poisson regression models. These models can be applied to continuous data with positive probability in zero, and they are characterized by the variance function that defines the mean-variance relationship. Formulas are obtained to apply local influence methods for different perturbations and it is of particular interest the perturbation of the parameter that defines the mean-variance relation. These schemes are applied to perturbed data generated by simulations and the sensibility of the method is compared for different values of the parameters. Finally, a real data set about home expenditures is analyzed and local influence graphics are obtained to detect influential points.
publishDate 2012
dc.date.none.fl_str_mv 2012-09
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 https://nulan.mdp.edu.ar/id/eprint/1805/
https://nulan.mdp.edu.ar/id/eprint/1805/1/ricci.alegre.2012.pdf
url https://nulan.mdp.edu.ar/id/eprint/1805/
https://nulan.mdp.edu.ar/id/eprint/1805/1/ricci.alegre.2012.pdf
dc.language.none.fl_str_mv spa
language spa
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Scientific Advances Publishers
publisher.none.fl_str_mv Scientific Advances Publishers
dc.source.none.fl_str_mv Journal of Statistics: Advances in Theory and Applications, 18(1), 37-56. ISSN 0975-1262
reponame:Nülan (UNMDP-FCEyS)
instname:Universidad Nacional de Mar del Plata. Facultad de Ciencias Económicas y Sociales
reponame_str Nülan (UNMDP-FCEyS)
collection Nülan (UNMDP-FCEyS)
instname_str Universidad Nacional de Mar del Plata. Facultad de Ciencias Económicas y Sociales
repository.name.fl_str_mv Nülan (UNMDP-FCEyS) - Universidad Nacional de Mar del Plata. Facultad de Ciencias Económicas y Sociales
repository.mail.fl_str_mv cendocu@mdp.edu.ar
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score 12.993085

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