A Class of Hartley-Ross-Type Estimators for Population Mean in Adaptive and Stratified Adaptive Cluster Sampling

被引：2
|
作者：
Younis, Faryal [1 ]
Shabbir, Javid [1 ]
机构：
[1] Quaid I Azam Univ, Dept Stat, Islamabad, Pakistan
来源：
IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY TRANSACTION A-SCIENCE | 2019年 / 43卷 / A4期
关键词：
Adaptive cluster sampling; Auxiliary variable; Hartley-Ross; Bias; Mean square error; RATIO ESTIMATORS;
D O I：
10.1007/s40995-018-0552-6
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
In this article, we propose a class of Hartley-Ross-type unbiased estimators of finite population mean under adaptive cluster sampling and stratified adaptive cluster sampling. The estimators utilize information on known parameters of the auxiliary variable. The variances of proposed class of unbiased estimators are obtained up to first degree of approximation. Proposed estimators are more efficient than the usual mean estimator, ratio, and modified ratio estimators in adaptive cluster sampling and stratified adaptive cluster sampling under certain realistic conditions. Simulation study considering different populations is carried out to support the theoretical findings.
引用
收藏
页码：1619 / 1627
页数：9
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