Robust estimators in semi-functional partial linear regression models

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 eve...

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Detalles Bibliográficos
Autor principal: Boente, Graciela Lina
Publicado: 2017
Materias:
Functional data
Kernel smoothers
Partial linear models
Robust estimation
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_0047259X_v154_n_p59_Boente
http://hdl.handle.net/20.500.12110/paper_0047259X_v154_n_p59_Boente
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_0047259X_v154_n_p59_Boente
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spelling paper:paper_0047259X_v154_n_p59_Boente2023-06-08T15:05:36Z Robust estimators in semi-functional partial linear regression models Boente, Graciela Lina Functional data Kernel smoothers Partial linear models Robust estimation 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. Fil:Boente, G. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2017 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_0047259X_v154_n_p59_Boente http://hdl.handle.net/20.500.12110/paper_0047259X_v154_n_p59_Boente
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Functional data
Kernel smoothers
Partial linear models
Robust estimation
spellingShingle Functional data
Kernel smoothers
Partial linear models
Robust estimation
Boente, Graciela Lina
Robust estimators in semi-functional partial linear regression models
topic_facet Functional data
Kernel smoothers
Partial linear models
Robust estimation
description 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.
author Boente, Graciela Lina
author_facet Boente, Graciela Lina
author_sort Boente, Graciela Lina
title Robust estimators in semi-functional partial linear regression models
title_short Robust estimators in semi-functional partial linear regression models
title_full Robust estimators in semi-functional partial linear regression models
title_fullStr Robust estimators in semi-functional partial linear regression models
title_full_unstemmed Robust estimators in semi-functional partial linear regression models
title_sort robust estimators in semi-functional partial linear regression models
publishDate 2017
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_0047259X_v154_n_p59_Boente
http://hdl.handle.net/20.500.12110/paper_0047259X_v154_n_p59_Boente
work_keys_str_mv AT boentegracielalina robustestimatorsinsemifunctionalpartiallinearregressionmodels
_version_ 1768542638043037696

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