The New Sub-Regression Type Estimator in Ranked Set Sampling

Koçyiğit, EDA; Rather, Khalid-Ul

doi:10.1007/s42519-023-00324-9

The New Sub-Regression Type Estimator in Ranked Set Sampling

Atıf İçin Kopyala

Koçyiğit E. G., Rather K. I.

JOURNAL OF STATISTICAL THEORY AND PRACTICE, cilt.0, ss.17-27, 2023 (ESCI)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 0
Basım Tarihi: 2023
Doi Numarası: 10.1007/s42519-023-00324-9
Dergi Adı: JOURNAL OF STATISTICAL THEORY AND PRACTICE
Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, zbMATH
Sayfa Sayıları: ss.17-27
Dokuz Eylül Üniversitesi Adresli: Evet

Özet

In this study, a new sub-regression type estimator for ranked set sampling (RSS) is proposed based on the idea of a sub-ratio estimator given in Koçyiğit and Kadılar (2022). The proposed unbiased estimator's mean square error (MSE) is obtained and compared theoretically with other estimators. The theoretical results have been supported by the different simulations and real-life data sets studies and have shown that the proposed estimator is more effective than the estimators in the literature. It is also seen that the number of repetitions in the RSS affected the effectiveness of the sub-estimators.