Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Some efficient ratio-type exponential estimators using the Robust regression's Huber M-estimation function

  • Vinay Kumar Yadav (Department of Basic and Applied Science, National Institute of Technology Arunachal Pradesh) ;
  • Shakti Prasad (Department of Mathematics, National Institute of Technology Jamshedpur)
  • Received : 2023.06.16
  • Accepted : 2023.12.16
  • Published : 2024.05.31
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Abstract

The current article discusses ratio type exponential estimators for estimating the mean of a finite population in sample surveys. The estimators uses robust regression's Huber M-estimation function, and their bias as well as mean squared error expressions are derived. It was campared with Kadilar, Candan, and Cingi (Hacet J Math Stat, 36, 181-188, 2007) estimators. The circumstances under which the suggested estimators perform better than competing estimators are discussed. Five different population datasets with a well recognized outlier have been widely used in numerical and simulation-based research. These thorough studies seek to provide strong proof to back up our claims by carefully assessing and validating the theoretical results reported in our study. The estimators that have been proposed are intended to significantly improve both the efficiency and accuracy of estimating the mean of a finite population. As a result, the results that are obtained from statistical analyses will be more reliable and precise.

Keywords

Acknowledgement

Authors are thankful to the Editor-in-Chief and learned referees for their inspiring and fruitful suggestions. The authors are also thankful to the National Institute of Technology Arunachal Pradesh, Jote, for providing the necessary infrastructure for the completion of the present work.

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