Enhancing minimum vector variance estimators using reweighted scheme

Minimum vector variance (MVV) is one of the latest contributions in the study of multivariate robust estimators.MVV estimators possess three important properties of a good robust estimator, namely, high breakdown point, affine equivariance and computational efficiency.However, highly robust affine e...

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Main Authors: Ali, Hazlina, Syed Yahaya, Sharipah Soaad, Omar, Zurni
Format: Article
Published: Pushpa Publishing House 2015
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Online Access:http://repo.uum.edu.my/16531/
http://doi.org/10.17654/FJMSDec2015_819_830
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Institution: Universiti Utara Malaysia
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spelling my.uum.repo.165312016-04-27T01:04:27Z http://repo.uum.edu.my/16531/ Enhancing minimum vector variance estimators using reweighted scheme Ali, Hazlina Syed Yahaya, Sharipah Soaad Omar, Zurni QA Mathematics Minimum vector variance (MVV) is one of the latest contributions in the study of multivariate robust estimators.MVV estimators possess three important properties of a good robust estimator, namely, high breakdown point, affine equivariance and computational efficiency.However, highly robust affine equivariant estimators with the best breakdown point commonly have to compensate with low statistical efficiency.In order to cater this drawback, a reweighted minimum vector variance (RMVV) which is capable of increasing the efficiency while retaining the highest breakdown point is proposed in this paper.A simulation study was conducted to investigate the asymptotic relative efficiency and finite-sample behavior of the estimators for several types of distributions. The numerical results revealed that the reweighed scheme is able to attain higher efficiency compared to MVV estimators. Pushpa Publishing House 2015 Article PeerReviewed Ali, Hazlina and Syed Yahaya, Sharipah Soaad and Omar, Zurni (2015) Enhancing minimum vector variance estimators using reweighted scheme. Far East Journal of Mathematical Sciences (FJMS), 98 (7). pp. 819-830. ISSN 0972-0871 http://doi.org/10.17654/FJMSDec2015_819_830 doi:10.17654/FJMSDec2015_819_830
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
topic QA Mathematics
spellingShingle QA Mathematics
Ali, Hazlina
Syed Yahaya, Sharipah Soaad
Omar, Zurni
Enhancing minimum vector variance estimators using reweighted scheme
description Minimum vector variance (MVV) is one of the latest contributions in the study of multivariate robust estimators.MVV estimators possess three important properties of a good robust estimator, namely, high breakdown point, affine equivariance and computational efficiency.However, highly robust affine equivariant estimators with the best breakdown point commonly have to compensate with low statistical efficiency.In order to cater this drawback, a reweighted minimum vector variance (RMVV) which is capable of increasing the efficiency while retaining the highest breakdown point is proposed in this paper.A simulation study was conducted to investigate the asymptotic relative efficiency and finite-sample behavior of the estimators for several types of distributions. The numerical results revealed that the reweighed scheme is able to attain higher efficiency compared to MVV estimators.
format Article
author Ali, Hazlina
Syed Yahaya, Sharipah Soaad
Omar, Zurni
author_facet Ali, Hazlina
Syed Yahaya, Sharipah Soaad
Omar, Zurni
author_sort Ali, Hazlina
title Enhancing minimum vector variance estimators using reweighted scheme
title_short Enhancing minimum vector variance estimators using reweighted scheme
title_full Enhancing minimum vector variance estimators using reweighted scheme
title_fullStr Enhancing minimum vector variance estimators using reweighted scheme
title_full_unstemmed Enhancing minimum vector variance estimators using reweighted scheme
title_sort enhancing minimum vector variance estimators using reweighted scheme
publisher Pushpa Publishing House
publishDate 2015
url http://repo.uum.edu.my/16531/
http://doi.org/10.17654/FJMSDec2015_819_830
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