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Enhancing minimum vector variance estimators using reweighted scheme

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

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Abstract

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.

Item Type: Article
Uncontrolled Keywords: Minimum vector variance; Outliers’ detection; Reweighted minimum vector variance; Robust estimation
Subjects: Q Science > QA Mathematics
Divisions: School of Computing
Depositing User: Dr. Hazlina Ali
Date Deposited: 20 Dec 2015 07:45
Last Modified: 27 Apr 2016 01:04
URI: https://repo.uum.edu.my/id/eprint/16531

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