Robust three-step regression based on comedian and its performance in cell-wise and case-wise outliers

Henry Velasco, Henry Laniado, Mauricio Toro, VICTOR ELISEO LEIVA SANCHEZ, Yuhlong Lio

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

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 languageEnglish
Article number1259
JournalMathematics
Volume8
Issue number8
DOIs
StatePublished - Aug 2020
Externally publishedYes

Keywords

  • 3S-regression
  • Case-wise contamination
  • Comedian
  • MAD
  • Monte carlo simulation
  • R software
  • Robustness
  • Rocke S-estimator

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