Testing in generalized partially linear models: A robust approach
In this paper, we introduce a family of robust statistics which allow to decide between a parametric model and a semiparametric one. More precisely, under a generalized partially linear model, i.e., when the observations satisfy y i(x i,t i)F(i) with μ i = H((t i)+x i t) and H a known link function,...
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Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_01677152_v83_n1_p203_Boente |
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todo:paper_01677152_v83_n1_p203_Boente2023-10-03T15:05:16Z Testing in generalized partially linear models: A robust approach Boente, G. Cao, R. González Manteiga Wenceslao, W. Rodriguez, D. Generalized partially linear models Kernel weights Rate of convergence Robust testing In this paper, we introduce a family of robust statistics which allow to decide between a parametric model and a semiparametric one. More precisely, under a generalized partially linear model, i.e., when the observations satisfy y i(x i,t i)F(i) with μ i = H((t i)+x i t) and H a known link function, we want to test H0:(t)=+t against H1:is a nonlinear smooth function. A general approach which includes robust estimators based on a robustified deviance or a robustified quasi-likelihood is considered. The asymptotic behavior of the test statistic under the null hypothesis is obtained. © 2012 Elsevier B.V. Fil:Boente, G. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Rodriguez, D. 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_01677152_v83_n1_p203_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 |
Generalized partially linear models Kernel weights Rate of convergence Robust testing |
spellingShingle |
Generalized partially linear models Kernel weights Rate of convergence Robust testing Boente, G. Cao, R. González Manteiga Wenceslao, W. Rodriguez, D. Testing in generalized partially linear models: A robust approach |
topic_facet |
Generalized partially linear models Kernel weights Rate of convergence Robust testing |
description |
In this paper, we introduce a family of robust statistics which allow to decide between a parametric model and a semiparametric one. More precisely, under a generalized partially linear model, i.e., when the observations satisfy y i(x i,t i)F(i) with μ i = H((t i)+x i t) and H a known link function, we want to test H0:(t)=+t against H1:is a nonlinear smooth function. A general approach which includes robust estimators based on a robustified deviance or a robustified quasi-likelihood is considered. The asymptotic behavior of the test statistic under the null hypothesis is obtained. © 2012 Elsevier B.V. |
format |
JOUR |
author |
Boente, G. Cao, R. González Manteiga Wenceslao, W. Rodriguez, D. |
author_facet |
Boente, G. Cao, R. González Manteiga Wenceslao, W. Rodriguez, D. |
author_sort |
Boente, G. |
title |
Testing in generalized partially linear models: A robust approach |
title_short |
Testing in generalized partially linear models: A robust approach |
title_full |
Testing in generalized partially linear models: A robust approach |
title_fullStr |
Testing in generalized partially linear models: A robust approach |
title_full_unstemmed |
Testing in generalized partially linear models: A robust approach |
title_sort |
testing in generalized partially linear models: a robust approach |
url |
http://hdl.handle.net/20.500.12110/paper_01677152_v83_n1_p203_Boente |
work_keys_str_mv |
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_version_ |
1807315804065103872 |