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dc.contributor.author
Bianco, Ana Maria
dc.contributor.author
Boente Boente, Graciela Lina
dc.contributor.author
Rodrigues, Isabel
dc.date.available
2017-05-02T18:01:43Z
dc.date.issued
2013-02
dc.identifier.citation
Bianco, Ana Maria; Boente Boente, Graciela Lina; Rodrigues, Isabel; Resistant estimators in Poisson and Gamma models with missing responses and an application to outlier detection; Elsevier Inc; Journal Of Multivariate Analysis; 114; 2-2013; 209-226
dc.identifier.issn
0047-259X
dc.identifier.uri
http://hdl.handle.net/11336/15863
dc.description.abstract
When dealing with situations in which the responses are discrete or show some type of asymmetry, the linear model is not appropriate to establish the relation between the responses and the covariates. Generalized linear models serve this purpose, since they allow one to model the mean of the responses through a link function, linearly on the covariates. When atypical observations are present in the sample, robust estimators are useful to provide fair estimations as well as to build outlier detection rules. The focus of this paper is to define robust estimators for the regression parameter when missing data possibly occur in the responses. The estimators introduced turn out to be consistent under mild conditions. In particular, resistant methods for Poisson and Gamma models are given. A simulation study allows one to compare the behaviour of the classical and robust estimators, under different contamination schemes. The robustness of the proposed procedures is studied through the influence function, while asymptotic variances are derived from it. Besides, outlier detection rules are defined using the influence function. The procedure is also illustrated by analysing a real data set.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier Inc
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.subject
Fisher-Consistency
dc.subject
Generalized Lnear Model
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Missing Data
dc.subject
Outliers
dc.subject.classification
Estadística y Probabilidad
dc.subject.classification
Matemáticas
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Resistant estimators in Poisson and Gamma models with missing responses and an application to outlier detection
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2017-04-28T20:29:24Z
dc.journal.volume
114
dc.journal.pagination
209-226
dc.journal.pais
Estados Unidos
dc.journal.ciudad
Nueva York
dc.description.fil
Fil: Bianco, Ana Maria. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: Boente Boente, Graciela Lina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: Rodrigues, Isabel. Technical University of Lisbon; Portugal
dc.journal.title
Journal Of Multivariate Analysis
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.jmva.2012.08.008
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0047259X12002060


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