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Abstract:

Partial linear models have been adapted to deal with functional covariates to capture both the advantages of a semi-linear modelling and those of nonparametric modelling for functional data. It is easy to see that the estimation procedures for these models are highly sensitive to the presence of even a small proportion of outliers in the data. To solve the problem of atypical observations when the covariates of the nonparametric component are functional, robust estimates for the regression parameter and regression operator are introduced. Consistency results of the robust estimators and the asymptotic distribution of the regression parameter estimator are studied. The reported numerical experiments show that the resulting estimators have good robustness properties. The benefits of considering robust estimators is also illustrated on a real data set where the robust fit reveals the presence of influential outliers. © 2016 Elsevier Inc.

Registro:

Documento: Artículo
Título:Robust estimators in semi-functional partial linear regression models
Autor:Boente, G.; Vahnovan, A.
Filiación:Departamento de Matemáticas, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 1, Buenos Aires, 1428, Argentina
IMAS, CONICET, Ciudad Universitaria, Pabellón 1, Buenos Aires, 1428, Argentina
Departamento de Matemáticas, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Calle 50 y 115, La Plata, Argentina
CONICET, Godoy Cruz 2290. 1425, Buenos Aires, Argentina
Palabras clave:Functional data; Kernel smoothers; Partial linear models; Robust estimation
Año:2017
Volumen:154
Página de inicio:59
Página de fin:84
DOI: http://dx.doi.org/10.1016/j.jmva.2016.10.005
Título revista:Journal of Multivariate Analysis
Título revista abreviado:J. Multivariate Anal.
ISSN:0047259X
CODEN:JMVAA
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_0047259X_v154_n_p59_Boente

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Citas:

---------- APA ----------
Boente, G. & Vahnovan, A. (2017) . Robust estimators in semi-functional partial linear regression models. Journal of Multivariate Analysis, 154, 59-84.
http://dx.doi.org/10.1016/j.jmva.2016.10.005
---------- CHICAGO ----------
Boente, G., Vahnovan, A. "Robust estimators in semi-functional partial linear regression models" . Journal of Multivariate Analysis 154 (2017) : 59-84.
http://dx.doi.org/10.1016/j.jmva.2016.10.005
---------- MLA ----------
Boente, G., Vahnovan, A. "Robust estimators in semi-functional partial linear regression models" . Journal of Multivariate Analysis, vol. 154, 2017, pp. 59-84.
http://dx.doi.org/10.1016/j.jmva.2016.10.005
---------- VANCOUVER ----------
Boente, G., Vahnovan, A. Robust estimators in semi-functional partial linear regression models. J. Multivariate Anal. 2017;154:59-84.
http://dx.doi.org/10.1016/j.jmva.2016.10.005