New Exponential Ratio Estimator in Ranked Set Sampling

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Rather K. U. I., KOÇYİĞİT E. G., Unal C., Jeelani M. I.

PAKISTAN JOURNAL OF STATISTICS AND OPERATION RESEARCH, vol.18, no.2, pp.403-409, 2022 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 18 Issue: 2
  • Publication Date: 2022
  • Doi Number: 10.18187/pjsor.v18i2.3921
  • Journal Name: PAKISTAN JOURNAL OF STATISTICS AND OPERATION RESEARCH
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, Academic Search Premier, zbMATH
  • Page Numbers: pp.403-409
  • Keywords: Exponential ratio estimator, ranked set sampling, mean square error (MSE), efficiency
  • Hacettepe University Affiliated: Yes

Abstract

In this study, we adapted the families of estimators from Unal and Kadilar (2021) using the exponential function for the population mean in case of non-response for simple random sampling for the estimation of the mean of the population with the RSS (ranked set sampling) method. The equations for the MSE (mean square error) and the bias of the adapted estimators are obtained for RSS and it in theory shows that the proposed estimator is additional efficient than the present RSS mean estimators in the literature. In addition, we support these theoretical results with real COVID-19 real data and conjointly the simulation studies with different distributions and parameters. As a result of the study, it was observed that the efficiency of the proposed estimator was better than the other estimators.