Robust estimates in generalized partially linear models

In this paper, we introduce a family of robust estimates for the parametric and nonparametric components under a generalized partially linear model, where the data are modeled by y i |(x i , t i ) ∼ F (·, μ i ) with μ i = H(η(t i ) + x i T β), with for some known distribution function F and link fun...

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Detalles Bibliográficos
Autor principal: Boente, Graciela Lina
Publicado: 2006
Materias:
Kernel weights
Partially linear models
Rate of convergence
Robust estimation
Smoothing
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00905364_v34_n6_p2856_Boente
http://hdl.handle.net/20.500.12110/paper_00905364_v34_n6_p2856_Boente
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_00905364_v34_n6_p2856_Boente
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spelling paper:paper_00905364_v34_n6_p2856_Boente2023-06-08T15:07:50Z Robust estimates in generalized partially linear models Boente, Graciela Lina Kernel weights Partially linear models Rate of convergence Robust estimation Smoothing In this paper, we introduce a family of robust estimates for the parametric and nonparametric components under a generalized partially linear model, where the data are modeled by y i |(x i , t i ) ∼ F (·, μ i ) with μ i = H(η(t i ) + x i T β), with for some known distribution function F and link function H. It is shown that the estimates of β are root-n consistent and asymptotically normal. Through a Monte Carlo study, the performance of these estimators is compared with that of the classical ones. © Institute of Mathematical Statistics, 2006. Fil:Boente, G. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2006 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00905364_v34_n6_p2856_Boente http://hdl.handle.net/20.500.12110/paper_00905364_v34_n6_p2856_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 Kernel weights
Partially linear models
Rate of convergence
Robust estimation
Smoothing
spellingShingle Kernel weights
Partially linear models
Rate of convergence
Robust estimation
Smoothing
Boente, Graciela Lina
Robust estimates in generalized partially linear models
topic_facet Kernel weights
Partially linear models
Rate of convergence
Robust estimation
Smoothing
description In this paper, we introduce a family of robust estimates for the parametric and nonparametric components under a generalized partially linear model, where the data are modeled by y i |(x i , t i ) ∼ F (·, μ i ) with μ i = H(η(t i ) + x i T β), with for some known distribution function F and link function H. It is shown that the estimates of β are root-n consistent and asymptotically normal. Through a Monte Carlo study, the performance of these estimators is compared with that of the classical ones. © Institute of Mathematical Statistics, 2006.
author Boente, Graciela Lina
author_facet Boente, Graciela Lina
author_sort Boente, Graciela Lina
title Robust estimates in generalized partially linear models
title_short Robust estimates in generalized partially linear models
title_full Robust estimates in generalized partially linear models
title_fullStr Robust estimates in generalized partially linear models
title_full_unstemmed Robust estimates in generalized partially linear models
title_sort robust estimates in generalized partially linear models
publishDate 2006
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00905364_v34_n6_p2856_Boente
http://hdl.handle.net/20.500.12110/paper_00905364_v34_n6_p2856_Boente
work_keys_str_mv AT boentegracielalina robustestimatesingeneralizedpartiallylinearmodels
_version_ 1768545088062881792

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