Abstract
Both cell-wise and case-wise outliers may appear in a real data set at the same time. Few methods have been developed in order to deal with both types of outliers when formulating a regression model. In this work, a robust estimator is proposed based on a three-step method named 3S-regression, which uses the comedian as a highly robust scatter estimate. An intensive simulation study is conducted in order to evaluate the performance of the proposed comedian 3S-regression estimator in the presence of cell-wise and case-wise outliers. In addition, a comparison of this estimator with recently developed robust methods is carried out. The proposed method is also extended to the model with continuous and dummy covariates. Finally, a real data set is analyzed for illustration in order to show potential applications.
Original language | English |
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Article number | 1259 |
Journal | Mathematics |
Volume | 8 |
Issue number | 8 |
DOIs | |
State | Published - Aug 2020 |
Keywords
- 3S-regression
- Case-wise contamination
- Comedian
- MAD
- Monte carlo simulation
- R software
- Robustness
- Rocke S-estimator