Abstract

In this paper, a class of hybrid type estimators is proposed in estimating the finite population variance using single auxiliary variable in simple random sampling. Expressions for the bias and the mean square error (MSE) are derived up to the first order of approximation. Theoretically comparisons are provided to show that the proposed estimators perform more efficiently than various existing estimators. Empirical study and simulation results are carried out to confirm numerically that the proposed estimators are more efficient than the usual unbiased sample variance estimator, ratio and linear regression estimators by Isaki, Singh et al., and Shabbir and Gupta estimators.

摘要

本文提出了一类混合型估计量，用于在简单随机抽样中使用单个辅助变量估计有限总体方差。偏差和均方误差 (MSE) 的表达式可以推导出到一阶近似值。提供了理论上的比较，以表明所提出的估计器比各种现有的估计器执行得更有效。实证研究和模拟结果在数值上证实了所提出的估计器比 Isaki、Singh 等人的常用无偏样本方差估计器、比率和线性回归估计器以及 Shabbir 和 Gupta 估计器更有效。