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dc.contributor.author
Muler, Nora  
dc.contributor.author
Yohai, Victor Jaime  
dc.date.available
2017-05-02T21:41:51Z  
dc.date.issued
2013-09  
dc.identifier.citation
Muler, Nora; Yohai, Victor Jaime; Robust estimation for vector autoregressive models; Elsevier Science; Computational Statistics And Data Analysis; 65; 9-2013; 68-79  
dc.identifier.issn
0167-9473  
dc.identifier.uri
http://hdl.handle.net/11336/15912  
dc.description.abstract
A new class of robust estimators for VAR models is introduced. These estimators are an extension to the multivariate case of the MM-estimators based on a bounded innovation propagation AR model. They have a filtering mechanism that avoids the propagation of the effect of one outlier to the residuals of the subsequent periods. Besides, they are consistent and have the same asymptotic normal distribution as regular MM-estimators for VAR models. A Monte Carlo study shows that these estimators compare favorable with respect to other robust ones.  
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
Robust Estimators  
dc.subject
Bmm-Estimator  
dc.subject
Var Models  
dc.subject.classification
Estadística y Probabilidad  
dc.subject.classification
Matemáticas  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Robust estimation for vector autoregressive 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
2017-05-02T20:59:04Z  
dc.journal.volume
65  
dc.journal.pagination
68-79  
dc.journal.pais
Países Bajos  
dc.journal.ciudad
Amsterdam  
dc.description.fil
Fil: Muler, Nora. Universidad Torcuato Di Tella. Departamento de Matemáticas y Estadística; Argentina  
dc.description.fil
Fil: Yohai, Victor Jaime. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; 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.2012.02.011  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S016794731200093X  

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