A new class of regression cum ratio estimators of population mean in ranked set sampling

被引：0
|
作者：
Lakhkar Khan
Javid Shabbir
Alamgir Khalil
机构：
[1] Higher Education Department,Department of Statistics
[2] Quaid-i-Azam University,Department of Statistics
[3] University of Peshawar,undefined
来源：
Life Cycle Reliability and Safety Engineering | 2019年 / 8卷 / 3期
关键词：
Regression estimators; Mean squared error; Transformed auxiliary information; Ranked set sampling;
D O I：
10.1007/s41872-019-00079-y
中图分类号：
学科分类号：
摘要：
This study proposes a new class of regression cum ratio estimators, using transformation of the auxiliary variables. The expressions for the biases and mean squared errors of the new class of estimators are derived in the study. Both the theoretical and numerical comparison of the proposed estimators and their respective competitive estimators are made. To check the performance of estimators, a simulation study was performed. The performance of the new class of estimators was assessed and proven better in comparison to their competitive estimators.
引用
收藏
页码：201 / 204
页数：3
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