A simulation study: Robust ratio double sampling estimator of finite population mean in the presence of outliers

Document Type : Research Note

Authors

1 Faculty of Science, Department of Statistics, Cankiri Karatekin University,18100 Cankiri, Turkey

2 Faculty of Science, Department of Statistics, Ondokuz Mayis University, 55139 Samsun, Turkey

Abstract

In this study, we suggest a family of ratio estimators for the population mean parameter using various robust regression techniques. These robust regressions techniques are Huber MM, LTS, and LMS estimates. We evaluate the performance of estimators in terms of the mean square error (MSE), and we compare the efficiency of our proposed robust-regression-ratio-type estimators with existing estimators under the optimal conditions. These comparisons show that our robust ratio-type estimators give more efficient results than the existing estimators under double sampling. In addition, the simulation and the empirical studies based on a data set that includes unusual observations show that our proposed estimators have a lower MSE than the existing estimators.

Keywords

References

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Scientia Iranica
Volume 31, Issue 15
Transactions on Industrial Engineering (E)
July and August 2024
Pages 1330-1341

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History

  • Receive Date: 17 April 2020
  • Revise Date: 25 July 2021
  • Accept Date: 04 October 2021

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