Robust estimates for ARMA models

Two new classes of robust estimates for ARMA models are introduced: estimates based on residual autocovariances (RA estimates), and estimates based on truncated residual autocovariances (TRA estimates). A heuristic derivation of the asymptotic normal distribution is given. We also perform a Monte Ca...

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Guardado en:
Detalles Bibliográficos
Publicado: 1986
Materias:
Monte carlo
Robust estimation
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01621459_v81_n393_p155_Bustos
http://hdl.handle.net/20.500.12110/paper_01621459_v81_n393_p155_Bustos
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_01621459_v81_n393_p155_Bustos
record_format dspace
spelling paper:paper_01621459_v81_n393_p155_Bustos2023-06-08T15:13:39Z Robust estimates for ARMA models Monte carlo Robust estimation Two new classes of robust estimates for ARMA models are introduced: estimates based on residual autocovariances (RA estimates), and estimates based on truncated residual autocovariances (TRA estimates). A heuristic derivation of the asymptotic normal distribution is given. We also perform a Monte Carlo study to compare the robustness properties of these estimates with the least squares, M, and GM estimates. In this study we consider observations that correspond to a Gaussian model with additive outliers. The Monte Carlo results show that RA and TRA estimates compare favorably with respect to least squares, M, and GM estimates. © 1986 Taylor & Francis Group, LLC. 1986 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01621459_v81_n393_p155_Bustos http://hdl.handle.net/20.500.12110/paper_01621459_v81_n393_p155_Bustos
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Monte carlo
Robust estimation
spellingShingle Monte carlo
Robust estimation
Robust estimates for ARMA models
topic_facet Monte carlo
Robust estimation
description Two new classes of robust estimates for ARMA models are introduced: estimates based on residual autocovariances (RA estimates), and estimates based on truncated residual autocovariances (TRA estimates). A heuristic derivation of the asymptotic normal distribution is given. We also perform a Monte Carlo study to compare the robustness properties of these estimates with the least squares, M, and GM estimates. In this study we consider observations that correspond to a Gaussian model with additive outliers. The Monte Carlo results show that RA and TRA estimates compare favorably with respect to least squares, M, and GM estimates. © 1986 Taylor & Francis Group, LLC.
title Robust estimates for ARMA models
title_short Robust estimates for ARMA models
title_full Robust estimates for ARMA models
title_fullStr Robust estimates for ARMA models
title_full_unstemmed Robust estimates for ARMA models
title_sort robust estimates for arma models
publishDate 1986
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01621459_v81_n393_p155_Bustos
http://hdl.handle.net/20.500.12110/paper_01621459_v81_n393_p155_Bustos
_version_ 1768542640829104128

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