辅助属性存在下有限总体均值回归型估计的改进修正类

Awwal Adejumobi, M. A. Yunusa, Ahmed Audu
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引用次数: 0

摘要

本文提出了改进有限总体均值回归型估计的修正类的估计量。提出估计量的本质是基于研究变量与辅助属性之间可能存在弱关系的假设。利用泰勒级数方法得到了所提估计量的性质(偏差和均方误差)。建立了该估计器优于其他相关估计器的效率条件。实证研究结果是激励的,结果表明,与研究中考虑的现有估计器相比,所提出的估计器更精通。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved Modified Classes of Regression Type Estimators of Finite Population Mean in the Presence of Auxiliary Attribute
In this research, estimators are suggested to improve modified classes of regression type estimators of finite population mean. The essence of proposing the estimators is as a result of the assumption that there may be weak relationship between study variable and auxiliary attribute. Properties (Biases and MSEs) of the proposed estimators are procured using Taylor series method. The efficiency conditions under which the proposed estimators are better than other related ones are established. Empirical findings are incentive and the results shown that the proposed estimators are more proficient compare to the existing estimators considered in the study.
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