The Redescending M estimator For detection and deletion of Outliers in Regression analysis
Outliers in a statistical analysis strongly affect the performance of the ordinary least squares, such outliers need to be detected and extreme outliers deleted. Thisp is aimed at proposing a Redescending M-estimator which is more efficient and robust compared to other existing methods. The results...
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| Veröffentlicht in: | Pakistan journal of statistics and operation research 2021-12, Vol.17 (4), p.997-1014 |
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| container_title | Pakistan journal of statistics and operation research |
| container_volume | 17 |
| creator | Anekwe, Stella Onyeagu, Sidney |
| description | Outliers in a statistical analysis strongly affect the performance of the ordinary least squares, such outliers need to be detected and extreme outliers deleted. Thisp is aimed at proposing a Redescending M-estimator which is more efficient and robust compared to other existing methods. The results show that the proposed method is effective in detection and deletion of extreme outliers compared to the other existing ones. |
| doi_str_mv | 10.18187/pjsor.v17i4.3546 |
| format | Article |
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| identifier | ISSN: 1816-2711 |
| ispartof | Pakistan journal of statistics and operation research, 2021-12, Vol.17 (4), p.997-1014 |
| issn | 1816-2711 2220-5810 |
| language | eng |
| recordid | cdi_proquest_journals_2881883609 |
| source | EZB-FREE-00999 freely available EZB journals |
| subjects | Data analysis Deletion Efficiency Estimators Monte Carlo simulation Normal distribution Outliers (statistics) Regression analysis Statistical analysis |
| title | The Redescending M estimator For detection and deletion of Outliers in Regression analysis |
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