Estimation of Finite Population Variance Under Stratified Sampling Technique

被引:8
|
作者
Yasmeen, Uzma [1 ]
Noor-ul-Amin, Muhammad [2 ]
机构
[1] Univ Waterloo, Dept Stat & Actuarial Sci, Waterloo, ON, Canada
[2] Univ Lahore, Ctr Res Mol Med, Inst Mol Biol & Biotechnol, Lahore, Pakistan
来源
JOURNAL OF RELIABILITY AND STATISTICAL STUDIES | 2021年 / 14卷 / 02期
关键词
Exponential estimator; stratified sampling; auxiliary variables; relative efficiency; RATIO ESTIMATORS;
D O I
10.13052/jrss0974-8024.14210
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The efficiency of the study variable can be improved by incorporating the information from the known auxiliary variables. Usually two techniques ratio and regression estimation are used with the help of auxiliary information in different approaches to acquire the high precision of the estimators. Considering the very heterogeneous population to get the size of the sample it may be originating impossible to get a sufficiently accurate and precise estimate by taking the simple random sampling technique from the complete population. Occasionally taking sample issue may differ significantly in different part of the entire population. For example, under study population consists of people living in apartments, own homes, hospitals and prisons or people living in plain regions and hill regions so in such situations the stratified sampling is one of the most commonly used approach to get a representative sample in survey sampling from different cross units of the population. The present study is set out on the recommendation of generalized variance estimators for finite population variance incorporating stratified sampling scheme with the information of single and two transformed auxiliary variables. The expressions of bias and mean square error (MSE) are obtained for the advised exponential type estimators. The conditions are obtained for which the anticipated estimators are better than the usual estimator. An empirical and simulation study is conducted to prove the superiority of the recommended estimator.
引用
收藏
页码:565 / 584
页数:20
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