ROBUST REGRESSION TYPE ESTIMATORS FOR BODY MASS INDEX UNDER EXTREME RANKED SET AND QUARTILE RANKED SET SAMPLING

被引：0

作者：

Cetin, Arzu Ece ^{[1
]}

Koyuncu, Nursel ^{[2
]}

机构：

[1] Gebze Tech Univ, Dept Management, Kocaeli, Turkiye

[2] Hacettepe Univ, Dept Stat, Ankara, Turkiye

来源：

COMMUNICATIONS FACULTY OF SCIENCES UNIVERSITY OF ANKARA-SERIES A1 MATHEMATICS AND STATISTICS | 2024年 / 73卷 / 02期

关键词：

Robust regression estimators; extreme ranked set sampling; quartile ranked set sampling; percentage relative efficiency (PRE);

D O I：

10.31801/cfsuasmas.1373759

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

. Robust regression-type estimators of population mean that use auxiliary variable information are proposed by considering robust methods under extreme ranked set sampling (ERSS) and quartile ranked set sampling (QRSS). We have used the data concerning body mass index (BMI) for 800 people in Turkey in 2014. The real data example is applied to see efficiency of the estimators in ERSS and QRSS designs and it is found that the proposed estimators are better in these designs than the classical ranked set sampling (RSS) design. In addition, mean square error (MSE) and percent relative efficiency (PRE) are used to compare the performance of the adapted and proposed estimators.

引用

页码：336 / 348

页数：13

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