Journal of Statistical Theory and Practice

, Volume 9, Issue 2, pp 313–329 | Cite as

Information Theoretic Weighted Mean Based on Truncated Ranked Set Sampling

  • Amjad D. Al-Nasser
  • Amer I. Al-OmariEmail author


This article proposes using an information theoretic procedure in order to obtain an unbiased weighted mean estimator for the population mean when the data collection structure is truncated-based ranked set sampling. The performance of the proposed estimator is discussed along with its properties, and the optimal weights are computed by maximizing Shannon’s entropy. It is found that the weighted truncated-based ranked set sampling estimator is more accurate and more efficient than its unweighted counterpart or the simple random sampling-based estimators.


Maximum Entropy Ranked Set Sampling Relative Efficiency Shannon’s Entropy 

AMS Subject Classification



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Copyright information

© Grace Scientific Publishing 2015

Authors and Affiliations

  1. 1.Department of Statistics, Faculty of ScienceYarmouk UniversityIrbidJordan
  2. 2.Department of Mathematics, Faculty of ScienceAl al-Bayt UniversityMafraqJordan

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