Optimal robust M-estimates of location

We find optimal robust estimates for the location parameter of n independent measurements from a common distribution F that belongs to a contamination neighborhood of a normal distribution. We follow an asymptotic minimax approach similar to Huber's but work with full neighborhoods of the centr...

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Detalles Bibliográficos
Autores principales:	Fraiman, R., Yohai, V.J., Zamar, R.H.
Formato:	JOUR
Materias:	M-estimates Minimax intervals Robust location
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_00905364_v29_n1_p194_Fraiman
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	todo:paper_00905364_v29_n1_p194_Fraiman
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spelling	todo:paper_00905364_v29_n1_p194_Fraiman2023-10-03T14:54:40Z Optimal robust M-estimates of location Fraiman, R. Yohai, V.J. Zamar, R.H. M-estimates Minimax intervals Robust location We find optimal robust estimates for the location parameter of n independent measurements from a common distribution F that belongs to a contamination neighborhood of a normal distribution. We follow an asymptotic minimax approach similar to Huber's but work with full neighborhoods of the central parametric model including nonsymmetric distributions. Our optimal estimates minimize monotone functions of the estimate's asymptotic variance and bias, which include asymptotic approximations for the quantiles of the estimate's distribution. In particular, we obtain robust asymptotic confidence intervals of minimax length. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_00905364_v29_n1_p194_Fraiman
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	M-estimates Minimax intervals Robust location
spellingShingle	M-estimates Minimax intervals Robust location Fraiman, R. Yohai, V.J. Zamar, R.H. Optimal robust M-estimates of location
topic_facet	M-estimates Minimax intervals Robust location
description	We find optimal robust estimates for the location parameter of n independent measurements from a common distribution F that belongs to a contamination neighborhood of a normal distribution. We follow an asymptotic minimax approach similar to Huber's but work with full neighborhoods of the central parametric model including nonsymmetric distributions. Our optimal estimates minimize monotone functions of the estimate's asymptotic variance and bias, which include asymptotic approximations for the quantiles of the estimate's distribution. In particular, we obtain robust asymptotic confidence intervals of minimax length.
format	JOUR
author	Fraiman, R. Yohai, V.J. Zamar, R.H.
author_facet	Fraiman, R. Yohai, V.J. Zamar, R.H.
author_sort	Fraiman, R.
title	Optimal robust M-estimates of location
title_short	Optimal robust M-estimates of location
title_full	Optimal robust M-estimates of location
title_fullStr	Optimal robust M-estimates of location
title_full_unstemmed	Optimal robust M-estimates of location
title_sort	optimal robust m-estimates of location
url	http://hdl.handle.net/20.500.12110/paper_00905364_v29_n1_p194_Fraiman
work_keys_str_mv	AT fraimanr optimalrobustmestimatesoflocation AT yohaivj optimalrobustmestimatesoflocation AT zamarrh optimalrobustmestimatesoflocation
_version_	1782029167031746560

Optimal robust M-estimates of location

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