Robust ratio and product based estimators using known auxiliary information through modified maximum likelihood

IF 0.9 Q2 MATHEMATICS
Priyanka Chhaparwal, Sanjay Kumar
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引用次数: 0

Abstract

In this paper, we consider the situation where the underlying distribution of the study variable is not normally distributed. Under such situations, we propose ratio and product based estimators for the finite population mean in simple random sampling using known auxiliary information based on order statistics. We obtain the expressions for biases and mean square errors (MSEs) of the proposed estimators, which show that the proposed estimators have less MSEs and biases than other existing estimators. Simulations have been studied under various super-population models. A real life application is also provided. Robustness properties of the proposed estimators have been studied via simulations. Confidence intervals (CIs) show that the proposed estimators have shorter CIs of estimates than those of the existing estimators.

Abstract Image

利用修正极大似然的已知辅助信息的鲁棒比估计和基于乘积的估计
在本文中,我们考虑研究变量的底层分布不是正态分布的情况。在这种情况下,我们提出了基于序统计量的基于已知辅助信息的简单随机抽样有限总体均值的比率和乘积估计。我们得到了所提估计量的偏差和均方误差的表达式,表明所提估计量的偏差和均方误差比现有估计量小。在各种超级人口模型下进行了模拟研究。还提供了一个实际应用程序。通过仿真研究了所提估计器的鲁棒性。置信区间(ci)表明,所提估计量的ci值比现有估计量的ci值要短。
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来源期刊
Afrika Matematika
Afrika Matematika MATHEMATICS-
CiteScore
2.00
自引率
9.10%
发文量
96
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