Abstract

It is a common approach to adopt the statistical measures of the auxiliary variable such as correlation, coefficient of variation etc. for estimating the population mean. In this paper we propose novel estimators by adding an exponential parameter on the auxiliary variable. Theoretically, we obtain the mean square error (MSE) for all proposed estimators and we compare MSE equations of our proposed estimators and classical estimators. As a result of these comparisons, we observe that proposed estimators are always more efficient than classical estimators. These theoretical results are supported with the aid of a numerical and simulation examples.

中文翻译：

---

通过添加指数参数提出新颖的修正比率估计器

摘要

通常采用辅助变量的统计度量（如相关性，变异系数等）来估计总体均值。在本文中，我们通过在辅助变量上添加指数参数来提出新颖的估计器。从理论上讲，我们获得了所有拟议估算器的均方误差（MSE），并比较了拟议估算器和经典估算器的MSE方程。这些比较的结果是，我们观察到建议的估计器总是比经典的估计器更有效。这些理论结果借助一个数值和仿真示例得到支持。