Robust estimators under semi-parametric partly linear autoregression: Asymptotic behaviour and bandwidth selection

In this article, under a semi-parametric partly linear autoregression model, a family of robust estimators for the autoregression parameter and the autoregression function is studied. The proposed estimators are based on a three-step procedure, in which robust regression estimators and robust smooth...

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Autores principales: Bianco, Ana María, Boente, Graciela Lina
Publicado: 2007
Materias:
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01439782_v28_n2_p274_Bianco
http://hdl.handle.net/20.500.12110/paper_01439782_v28_n2_p274_Bianco
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id paper:paper_01439782_v28_n2_p274_Bianco
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spelling paper:paper_01439782_v28_n2_p274_Bianco2023-06-08T15:11:57Z Robust estimators under semi-parametric partly linear autoregression: Asymptotic behaviour and bandwidth selection Bianco, Ana María Boente, Graciela Lina Asymptotic properties Cross-validation Filtering Partly linear autoregression Prediction Rate of convergence Robust estimation Smoothing techniques In this article, under a semi-parametric partly linear autoregression model, a family of robust estimators for the autoregression parameter and the autoregression function is studied. The proposed estimators are based on a three-step procedure, in which robust regression estimators and robust smoothing techniques are combined. Asymptotic results on the autoregression estimators are derived. Besides combining robust procedures with M-smoothers, predicted values for the series and detection residuals, which allow to detect anomalous data, are introduced. Robust cross-validation methods to select the smoothing parameter are presented as an alternative to the classical ones, which are sensitive to outlying observations. A Monte Carlo study is conducted to compare the performance of the proposed criteria. Finally, the asymptotic distribution of the autoregression parameter estimator is stated uniformly over the smoothing parameter. © 2007 The Authors Journal compilation 2007 Blackwell Publishing Ltd. 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. 2007 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01439782_v28_n2_p274_Bianco http://hdl.handle.net/20.500.12110/paper_01439782_v28_n2_p274_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 Asymptotic properties
Cross-validation
Filtering
Partly linear autoregression
Prediction
Rate of convergence
Robust estimation
Smoothing techniques
spellingShingle Asymptotic properties
Cross-validation
Filtering
Partly linear autoregression
Prediction
Rate of convergence
Robust estimation
Smoothing techniques
Bianco, Ana María
Boente, Graciela Lina
Robust estimators under semi-parametric partly linear autoregression: Asymptotic behaviour and bandwidth selection
topic_facet Asymptotic properties
Cross-validation
Filtering
Partly linear autoregression
Prediction
Rate of convergence
Robust estimation
Smoothing techniques
description In this article, under a semi-parametric partly linear autoregression model, a family of robust estimators for the autoregression parameter and the autoregression function is studied. The proposed estimators are based on a three-step procedure, in which robust regression estimators and robust smoothing techniques are combined. Asymptotic results on the autoregression estimators are derived. Besides combining robust procedures with M-smoothers, predicted values for the series and detection residuals, which allow to detect anomalous data, are introduced. Robust cross-validation methods to select the smoothing parameter are presented as an alternative to the classical ones, which are sensitive to outlying observations. A Monte Carlo study is conducted to compare the performance of the proposed criteria. Finally, the asymptotic distribution of the autoregression parameter estimator is stated uniformly over the smoothing parameter. © 2007 The Authors Journal compilation 2007 Blackwell Publishing Ltd.
author Bianco, Ana María
Boente, Graciela Lina
author_facet Bianco, Ana María
Boente, Graciela Lina
author_sort Bianco, Ana María
title Robust estimators under semi-parametric partly linear autoregression: Asymptotic behaviour and bandwidth selection
title_short Robust estimators under semi-parametric partly linear autoregression: Asymptotic behaviour and bandwidth selection
title_full Robust estimators under semi-parametric partly linear autoregression: Asymptotic behaviour and bandwidth selection
title_fullStr Robust estimators under semi-parametric partly linear autoregression: Asymptotic behaviour and bandwidth selection
title_full_unstemmed Robust estimators under semi-parametric partly linear autoregression: Asymptotic behaviour and bandwidth selection
title_sort robust estimators under semi-parametric partly linear autoregression: asymptotic behaviour and bandwidth selection
publishDate 2007
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01439782_v28_n2_p274_Bianco
http://hdl.handle.net/20.500.12110/paper_01439782_v28_n2_p274_Bianco
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AT boentegracielalina robustestimatorsundersemiparametricpartlylinearautoregressionasymptoticbehaviourandbandwidthselection
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