Consistency of a numerical approximation to the first principal component projection pursuit estimator

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We generalize to functional data, the approach given by Croux and Ruiz-Gazen (1996) to compute robust projection-pursuit principal direction estimators, allowing also for smoothness in the estimators. Consistency of the approximated first principal direction estimator is derived. © 2014 Elsevier B.V...

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Detalles Bibliográficos
Autores principales: Bali, Juan Lucas, Boente, Graciela Lina
Publicado: 2014
Materias:
Fisher-consistency
Functional principal components
Outliers
Projection-pursuit
Robust estimation
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01677152_v94_n_p181_Bali
http://hdl.handle.net/20.500.12110/paper_01677152_v94_n_p181_Bali
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_01677152_v94_n_p181_Bali
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spelling paper:paper_01677152_v94_n_p181_Bali2023-06-08T15:16:52Z Consistency of a numerical approximation to the first principal component projection pursuit estimator Bali, Juan Lucas Boente, Graciela Lina Fisher-consistency Functional principal components Outliers Projection-pursuit Robust estimation We generalize to functional data, the approach given by Croux and Ruiz-Gazen (1996) to compute robust projection-pursuit principal direction estimators, allowing also for smoothness in the estimators. Consistency of the approximated first principal direction estimator is derived. © 2014 Elsevier B.V. Fil:Bali, J.L. 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. 2014 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01677152_v94_n_p181_Bali http://hdl.handle.net/20.500.12110/paper_01677152_v94_n_p181_Bali
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Fisher-consistency
Functional principal components
Outliers
Projection-pursuit
Robust estimation
spellingShingle Fisher-consistency
Functional principal components
Outliers
Projection-pursuit
Robust estimation
Bali, Juan Lucas
Boente, Graciela Lina
Consistency of a numerical approximation to the first principal component projection pursuit estimator
topic_facet Fisher-consistency
Functional principal components
Outliers
Projection-pursuit
Robust estimation
description We generalize to functional data, the approach given by Croux and Ruiz-Gazen (1996) to compute robust projection-pursuit principal direction estimators, allowing also for smoothness in the estimators. Consistency of the approximated first principal direction estimator is derived. © 2014 Elsevier B.V.
author Bali, Juan Lucas
Boente, Graciela Lina
author_facet Bali, Juan Lucas
Boente, Graciela Lina
author_sort Bali, Juan Lucas
title Consistency of a numerical approximation to the first principal component projection pursuit estimator
title_short Consistency of a numerical approximation to the first principal component projection pursuit estimator
title_full Consistency of a numerical approximation to the first principal component projection pursuit estimator
title_fullStr Consistency of a numerical approximation to the first principal component projection pursuit estimator
title_full_unstemmed Consistency of a numerical approximation to the first principal component projection pursuit estimator
title_sort consistency of a numerical approximation to the first principal component projection pursuit estimator
publishDate 2014
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01677152_v94_n_p181_Bali
http://hdl.handle.net/20.500.12110/paper_01677152_v94_n_p181_Bali
work_keys_str_mv AT balijuanlucas consistencyofanumericalapproximationtothefirstprincipalcomponentprojectionpursuitestimator
AT boentegracielalina consistencyofanumericalapproximationtothefirstprincipalcomponentprojectionpursuitestimator
_version_ 1768543224889081856

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