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International Conference on Soft Methods in Probability and Statistics

SMPS 2016: Soft Methods for Data Science pp 121–126Cite as

Combining the Information of Multiple Ranker in Ranked Set Sampling with Fuzzy Set Approach

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 456))

Abstract

Ranked set sampling (RSS) is a useful alternative sampling method for parameter estimation. Compared to other sampling methods, it uses the ranking information of the units in the ranking mechanism before the actual measurement. The ranking mechanism can be described as a visual inspection of an expert or a highly-correlated concomitant variable. Accuracy for ranking of the sample units affects the precision of the estimation. This study proposes an alternative approach, called Fuzzy-weighted Ranked Set Sampling (FwRSS), to RSS for dealing with the uncertainty in ranking using fuzzy set. It assumes that there are K (\(K>1\)) rankers for rank decisions and uses three different fuzzy norm operators to combine the decisions of all rankers in order to provide the accuracy of ranking. A simulation study is constructed to see the performance of the mean estimators based on RSS and FwRSS.

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References

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Acknowledgments

This study is supported by the Scientific and Technological Research Council of Turkey (TUBITAK-COST Grant No. 115F300) under ISCH COST Action IS1304.

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Authors and Affiliations

  1. Faculty of Science, Department of Statistics, Dokuz Eylul University, Buca, Izmir, Turkey

    Bekir Cetintav, Selma Gurler & Neslihan Demirel

  2. Faculty of Engineering, Department of Industrial Engineering, Izmir University, Uckuyular, Izmir, Turkey

    Gozde Ulutagay

Authors
  1. Bekir Cetintav
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  2. Selma Gurler
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  3. Neslihan Demirel
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  4. Gozde Ulutagay
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Corresponding author

Correspondence to Bekir Cetintav .

Editor information

Editors and Affiliations

  1. Department of Statistical Sciences, Sapienza University of Rome, Rome, Italy

    Maria Brigida Ferraro

  2. Department of Statistical Sciences, Sapienza University of Rome, Roma, Italy

    Paolo Giordani

  3. Dept of Basic & Applied Sciences Engg, Sapienza University of Rome, Rome, Italy

    Barbara Vantaggi

  4. Dept of Stoc Metds,Polish Academy of Sci, Systems Research Institute, Warsaw, Poland

    Marek Gagolewski

  5. Dept of Statis&OR and MD, Univ de Oviedo, Oviedo, Spain

    María Ángeles Gil

  6. Dept of Stoc Metds,Polish Aca of Science, Systems Res Inst, Warsaw, Poland

    Przemysław Grzegorzewski

  7. Sys Res Inti, Dept of Stoch Methods, Polish Acadmy Sci in Warsaw, Warsaw, Poland

    Olgierd Hryniewicz

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© 2017 Springer International Publishing Switzerland

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Cite this paper

Cetintav, B., Gurler, S., Demirel, N., Ulutagay, G. (2017). Combining the Information of Multiple Ranker in Ranked Set Sampling with Fuzzy Set Approach. In: Ferraro, M., et al. Soft Methods for Data Science. SMPS 2016. Advances in Intelligent Systems and Computing, vol 456. Springer, Cham. https://doi.org/10.1007/978-3-319-42972-4_15

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  • DOI: https://doi.org/10.1007/978-3-319-42972-4_15

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42971-7

  • Online ISBN: 978-3-319-42972-4

  • eBook Packages: EngineeringEngineering (R0)

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