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Preliminary estimators for robust non-linear regression estimation

In this paper, the robustness of weighted non-linear least-squares estimation based on some preliminary estimators is examined. The preliminary estimators are the L-norm estimates proposed by Schlossmacher, by El-Attar et al., by Koenker and Park, and by Lawrence and Arthur. A numerical example is p...

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第一著者: Midi, Habshah
フォーマット: 論文
出版事項: Carfax Publishing Company 1999
オンライン･アクセス:http://psasir.upm.edu.my/id/eprint/116283/
https://www.tandfonline.com/doi/abs/10.1080/02664769922250
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spelling my.upm.eprints.1162832025-03-24T08:00:11Z http://psasir.upm.edu.my/id/eprint/116283/ Preliminary estimators for robust non-linear regression estimation Midi, Habshah In this paper, the robustness of weighted non-linear least-squares estimation based on some preliminary estimators is examined. The preliminary estimators are the L-norm estimates proposed by Schlossmacher, by El-Attar et al., by Koenker and Park, and by Lawrence and Arthur. A numerical example is presented to compare the robustness of the weighted non-linear least-squares approach when based on the preliminary estimators of Schlossmacher (HS), El-Attar et al. (HEA), Koenker and Park (HKP), and Lawrence and Arthur (HLA). The study shows that the HEA estimator is as robust as the HKP estimator. However, the HEA estimator posed certain computational problems and required more storage and computing time. Carfax Publishing Company 1999 Article PeerReviewed Midi, Habshah (1999) Preliminary estimators for robust non-linear regression estimation. Journal of Applied Statistics, 26 (5). pp. 591-600. ISSN 0266-4763; eISSN: 0266-4763 https://www.tandfonline.com/doi/abs/10.1080/02664769922250 10.1080/02664769922250
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description In this paper, the robustness of weighted non-linear least-squares estimation based on some preliminary estimators is examined. The preliminary estimators are the L-norm estimates proposed by Schlossmacher, by El-Attar et al., by Koenker and Park, and by Lawrence and Arthur. A numerical example is presented to compare the robustness of the weighted non-linear least-squares approach when based on the preliminary estimators of Schlossmacher (HS), El-Attar et al. (HEA), Koenker and Park (HKP), and Lawrence and Arthur (HLA). The study shows that the HEA estimator is as robust as the HKP estimator. However, the HEA estimator posed certain computational problems and required more storage and computing time.
format Article
author Midi, Habshah
spellingShingle Midi, Habshah
Preliminary estimators for robust non-linear regression estimation
author_facet Midi, Habshah
author_sort Midi, Habshah
title Preliminary estimators for robust non-linear regression estimation
title_short Preliminary estimators for robust non-linear regression estimation
title_full Preliminary estimators for robust non-linear regression estimation
title_fullStr Preliminary estimators for robust non-linear regression estimation
title_full_unstemmed Preliminary estimators for robust non-linear regression estimation
title_sort preliminary estimators for robust non-linear regression estimation
publisher Carfax Publishing Company
publishDate 1999
url http://psasir.upm.edu.my/id/eprint/116283/
https://www.tandfonline.com/doi/abs/10.1080/02664769922250
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score 13.251813

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