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...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Published: |
Pushpa Publishing House
2015
|
| Subjects: |
| _version_ | 1825803722643472384 |
|---|---|
| author | Ali, Hazlina Syed Yahaya, Sharipah Soaad Omar, Zurni |
| author_facet | Ali, Hazlina Syed Yahaya, Sharipah Soaad Omar, Zurni |
| author_sort | Ali, Hazlina |
| collection | UUM |
| 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. |
| first_indexed | 2024-07-04T06:02:19Z |
| format | Article |
| id | uum-16531 |
| institution | Universiti Utara Malaysia |
| last_indexed | 2024-07-04T06:02:19Z |
| publishDate | 2015 |
| publisher | Pushpa Publishing House |
| record_format | eprints |
| spelling | uum-165312016-04-27T01:04:27Z https://repo.uum.edu.my/id/eprint/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 doi:10.17654/FJMSDec2015_819_830 |
| spellingShingle | QA Mathematics Ali, Hazlina Syed Yahaya, Sharipah Soaad Omar, Zurni Enhancing minimum vector variance estimators using reweighted scheme |
| title | 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_short | Enhancing minimum vector variance estimators using reweighted scheme |
| title_sort | enhancing minimum vector variance estimators using reweighted scheme |
| topic | QA Mathematics |
| work_keys_str_mv | AT alihazlina enhancingminimumvectorvarianceestimatorsusingreweightedscheme AT syedyahayasharipahsoaad enhancingminimumvectorvarianceestimatorsusingreweightedscheme AT omarzurni enhancingminimumvectorvarianceestimatorsusingreweightedscheme |