Robust estimates in generalized partially linear models

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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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Autores principales: Boente, G., He, X., Zhou, J.
Formato: JOUR
Materias:
Kernel weights
Partially linear models
Rate of convergence
Robust estimation
Smoothing
Acceso en línea: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 todo:paper_00905364_v34_n6_p2856_Boente
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spelling todo:paper_00905364_v34_n6_p2856_Boente2023-10-03T14:54:42Z Robust estimates in generalized partially linear models Boente, G. He, X. Zhou, J. 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. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar 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, G.
He, X.
Zhou, J.
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.
format JOUR
author Boente, G.
He, X.
Zhou, J.
author_facet Boente, G.
He, X.
Zhou, J.
author_sort Boente, G.
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
url http://hdl.handle.net/20.500.12110/paper_00905364_v34_n6_p2856_Boente
work_keys_str_mv AT boenteg robustestimatesingeneralizedpartiallylinearmodels
AT hex robustestimatesingeneralizedpartiallylinearmodels
AT zhouj robustestimatesingeneralizedpartiallylinearmodels
_version_ 1782025494878748672

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