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dc.contributor.author
Marazzi, Alfio Natale
dc.contributor.author
Valdora, Marina Silvia
dc.contributor.author
Yohai, Victor Jaime
dc.contributor.author
Amiguet, Michael
dc.date.available
2022-10-04T11:08:09Z
dc.date.issued
2019-03-12
dc.identifier.citation
Marazzi, Alfio Natale; Valdora, Marina Silvia; Yohai, Victor Jaime; Amiguet, Michael; A robust conditional maximum likelihood estimator for generalized linear models with a dispersion parameter; Springer; Test; 28; 1; 12-3-2019; 223-241
dc.identifier.issn
1133-0686
dc.identifier.uri
http://hdl.handle.net/11336/171617
dc.description.abstract
Highly robust and efficient estimators for generalized linear models with a dispersion parameter are proposed. The estimators are based on three steps. In the first step, the maximum rank correlation estimator is used to consistently estimate the slopes up to a scale factor. The scale factor, the intercept, and the dispersion parameter are robustly estimated using a simple regression model. Then, randomized quantile residuals based on the initial estimators are used to define a region S such that observations out of S are considered as outliers. Finally, a conditional maximum likelihood (CML) estimator given the observations in S is computed. We show that, under the model, S tends to the whole space for increasing sample size. Therefore, the CML estimator tends to the unconditional maximum likelihood estimator and this implies that this estimator is asymptotically fully efficient. Moreover, the CML estimator maintains the high degree of robustness of the initial one. The negative binomial regression case is studied in detail.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Springer
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
CONDITIONAL MAXIMUM LIKELIHOOD
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GENERALIZED LINEAR MODEL
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NEGATIVE BINOMIAL REGRESSION
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OVERDISPERSION
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ROBUST REGRESSION
dc.subject.classification
Estadística y Probabilidad
dc.subject.classification
Matemáticas
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
A robust conditional maximum likelihood estimator for generalized linear models with a dispersion parameter
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2022-09-30T20:18:24Z
dc.identifier.eissn
1863-8260
dc.journal.volume
28
dc.journal.number
1
dc.journal.pagination
223-241
dc.journal.pais
Alemania
dc.description.fil
Fil: Marazzi, Alfio Natale. Institut Universitaire de Médecine Sociale Et Préventive Lausanne; Suiza
dc.description.fil
Fil: Valdora, Marina Silvia. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; Argentina
dc.description.fil
Fil: Yohai, Victor Jaime. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; Argentina
dc.description.fil
Fil: Amiguet, Michael. Institut Universitaire de Médecine Sociale Et Préventive Lausanne; Suiza
dc.journal.title
Test
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://dx.doi.org/10.1007/s11749-018-0624-0
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://link.springer.com/article/10.1007/s11749-018-0624-0
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