Robust Regression-Ratio-Type Estimators of the Mean Utilizing Two Auxiliary Variables: A Simulation Study

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ZAMAN T., Dünder E., Audu A., Alilah D. A., Shahzad U., Hanif M.

MATHEMATICAL PROBLEMS IN ENGINEERING, vol.2021, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 2021
  • Publication Date: 2021
  • Doi Number: 10.1155/2021/6383927
  • Journal Name: MATHEMATICAL PROBLEMS IN ENGINEERING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, zbMATH, Directory of Open Access Journals, Civil Engineering Abstracts
  • Ondokuz Mayıs University Affiliated: Yes

Abstract

Many authors defined the modified version of the mean estimator by using two auxiliary variables. These proposed estimators highly depend on the calculated regression coefficients. In the presence of outliers, these estimators do not give satisfactory results. In this study, we improve the suggested estimators using several robust regression techniques while obtaining the regression coefficients. We compared the efficiencies between the suggested estimators and the estimators presented in the literature. We used two numerical examples and a simulation study to support these theoretical results. Empirical results show that the modified ratio estimator performs well in the presence of outliers when adopting robust regression techniques.