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dc.contributor.author
Bianco, Ana Maria  
dc.contributor.author
Spano, Paula Mercedes  
dc.date.available
2018-09-14T21:06:06Z  
dc.date.issued
2017-02  
dc.identifier.citation
Bianco, Ana Maria; Spano, Paula Mercedes; Robust estimation in partially linear errors-in-variables models; Elsevier Science; Computational Statistics and Data Analysis; 106; 2-2017; 46-64  
dc.identifier.issn
0167-9473  
dc.identifier.uri
http://hdl.handle.net/11336/59811  
dc.description.abstract
In many applications of regression analysis, there are covariates that are measured with errors. A robust family of estimators of the parametric and nonparametric components of a structural partially linear errors-in-variables model is introduced. The proposed estimators are based on a three-step procedure where robust orthogonal regression estimators are combined with robust smoothing techniques. Under regularity conditions, it is proved that the resulting estimators are consistent. The robustness of the proposal is studied by means of the empirical influence function when the linear parameter is estimated using the orthogonal M-estimator. A simulation study allows to compare the behaviour of the robust estimators with their classical relatives and a real example data is analysed to illustrate the performance of the proposal.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Elsevier Science  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/  
dc.subject
Fisher-Consistency  
dc.subject
Kernel Weights  
dc.subject
M-Location Functionals  
dc.subject
Nonparametric Regression  
dc.subject
Robust Estimation  
dc.subject.classification
Matemática Pura  
dc.subject.classification
Matemáticas  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Robust estimation in partially linear errors-in-variables models  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2018-09-14T14:27:03Z  
dc.journal.volume
106  
dc.journal.pagination
46-64  
dc.journal.pais
Países Bajos  
dc.journal.ciudad
Amsterdam  
dc.description.fil
Fil: Bianco, Ana Maria. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina  
dc.description.fil
Fil: Spano, Paula Mercedes. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina  
dc.journal.title
Computational Statistics and Data Analysis  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.csda.2016.09.002  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0167947316302109