Improved Estimation of Population Mean Through Known Conventional and Non-Conventional Measures of Auxiliary Variable

被引：0
作者：
Muhammad Irfan
Maria Javed
Zhengyan Lin
机构：
[1] Zhejiang University,Department of Mathematics, Institute of Statistics
[2] Government College University,Department of Statistics
来源：
Iranian Journal of Science and Technology, Transactions A: Science | 2019年 / 43卷
关键词：
Auxiliary variable; Bias; Exponential-type estimator; Mean squared error; Monte Carlo simulation; Study variable;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper proposes a generalized class of difference-cum-exponential-type estimators for population mean under simple random sampling without replacement through known conventional and non-conventional auxiliary information. It is observed that some well-known estimators are the members of our proposed class. Moreover, proposed class of estimators behaves efficiently than competing estimators under some simple conditions. Theoretical findings are confirmed with numerical illustration by using six real-life datasets. In addition, Monte Carlo simulation study on four real populations also approved the potential of the proposed class against competing estimators.
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页码：1851 / 1862
页数：11
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