A REGRESSION TYPE ESTIMATOR FOR MEAN ESTIMATION UNDER RANKED SET SAMPLING ALONGSIDE THE SENSITIVITY ISSUE


Shahzad U., Hanif M., KOYUNCU N. , Garcia Luengo A. V.

COMMUNICATIONS FACULTY OF SCIENCES UNIVERSITY OF ANKARA-SERIES A1 MATHEMATICS AND STATISTICS, cilt.68, ss.2037-2049, 2019 (ESCI İndekslerine Giren Dergi) identifier

  • Cilt numarası: 68 Konu: 2
  • Basım Tarihi: 2019
  • Doi Numarası: 10.31801/cfsuasmas.586057
  • Dergi Adı: COMMUNICATIONS FACULTY OF SCIENCES UNIVERSITY OF ANKARA-SERIES A1 MATHEMATICS AND STATISTICS
  • Sayfa Sayıları: ss.2037-2049

Özet

Koyuncu and Kadilar [7] introduced a family of estimators under simple random sampling. In this article; we adapt these estimators for ranked set sampling. Further, we suggest a regression-type estimator of population mean utilizing available supplementary information under ranked set sampling scheme alongside the sensitivity issue when the variate of interest is sensitive. The bias and mean square error of the suggested estimator is determined theoretically for both situations. A simulation study has been done to demonstrate the percentage relative efficiency of proposed estimators over the adapted and reviewed estimators.