Mean Estimation Based on FWA Using Ranked Set Sampling with Single and Multiple Rankers

Cetintav B., Ulutagay G., GÜRLER S., DEMİREL N.

16th International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems (IPMU), Eindhoven, Hollanda, 20 - 24 Haziran 2016, cilt.611, ss.790-797 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 611
  • Doi Numarası: 10.1007/978-3-319-40581-0_64
  • Basıldığı Şehir: Eindhoven
  • Basıldığı Ülke: Hollanda
  • Sayfa Sayıları: ss.790-797
  • Anahtar Kelimeler: Ranked set sampling, Uncertainty, Fuzzy sets, Fuzzy weighted average, Multiple rankers, FUZZY WEIGHTED AVERAGE, RANKINGS
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

The Ranked Set Sampling (RSS) is an advanced sampling method which improves the precision and accuracy of the mean estimator. In RSS, the units in the random sets which are drawn from a population are ranked by a ranking mechanism, and one of these ranked units is sampled from each set with a specific scheme. Ranking the units (visually or by a concomitant variable) could not be perfect because there is an uncertainty in decision making about the rank of a unit. In this study, we propose a fuzzy set perspective for RSS and an estimator for the population mean based on Fuzzy Weighted Average (FWA) operator. A real data application is given to illustrate the new approach for the single and multiple rankers.