Robust kernel estimators for additive models with dependent observations

Robust nonparametric estimators for additive regression or autoregression models under an α-mixing condition are proposed. They are based on local M-estimators or local medians with kernel weights, and their asymptotic behaviour is studied. Moreover, these local M-estimators achieve the same univari...

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Detalles Bibliográficos
Autores principales: Bianco, A., Boente, G.
Formato: JOUR
Materias:
Additive model
Kernel estimation
Nonparametric regression
Robust estimation
α-mixing conditions
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_03195724_v26_n2_p239_Bianco
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
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spelling todo:paper_03195724_v26_n2_p239_Bianco2023-10-03T15:23:13Z Robust kernel estimators for additive models with dependent observations Bianco, A. Boente, G. Additive model Kernel estimation Nonparametric regression Robust estimation α-mixing conditions Robust nonparametric estimators for additive regression or autoregression models under an α-mixing condition are proposed. They are based on local M-estimators or local medians with kernel weights, and their asymptotic behaviour is studied. Moreover, these local M-estimators achieve the same univariate rate of convergence as their linear relatives. Fil:Bianco, A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 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_03195724_v26_n2_p239_Bianco
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Additive model
Kernel estimation
Nonparametric regression
Robust estimation
α-mixing conditions
spellingShingle Additive model
Kernel estimation
Nonparametric regression
Robust estimation
α-mixing conditions
Bianco, A.
Boente, G.
Robust kernel estimators for additive models with dependent observations
topic_facet Additive model
Kernel estimation
Nonparametric regression
Robust estimation
α-mixing conditions
description Robust nonparametric estimators for additive regression or autoregression models under an α-mixing condition are proposed. They are based on local M-estimators or local medians with kernel weights, and their asymptotic behaviour is studied. Moreover, these local M-estimators achieve the same univariate rate of convergence as their linear relatives.
format JOUR
author Bianco, A.
Boente, G.
author_facet Bianco, A.
Boente, G.
author_sort Bianco, A.
title Robust kernel estimators for additive models with dependent observations
title_short Robust kernel estimators for additive models with dependent observations
title_full Robust kernel estimators for additive models with dependent observations
title_fullStr Robust kernel estimators for additive models with dependent observations
title_full_unstemmed Robust kernel estimators for additive models with dependent observations
title_sort robust kernel estimators for additive models with dependent observations
url http://hdl.handle.net/20.500.12110/paper_03195724_v26_n2_p239_Bianco
work_keys_str_mv AT biancoa robustkernelestimatorsforadditivemodelswithdependentobservations
AT boenteg robustkernelestimatorsforadditivemodelswithdependentobservations
_version_ 1807314777407488000

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