Abstract

We suggest a new class of difference-type estimators under two-phase stratified sampling when using information from two auxiliary variables including their distribution functions. The bias and MSE expressions are derived up to first degree of approximations. It is observed that the proposed class of difference-type estimators is more efficient as compared to the estimators: sample mean, ratio, exponential-ratio, traditional difference-types, Chand, Singh and Choudhury, and Anieting and Ezugwu regression type. The comparisons are made in Section 4 and results based on real data sets and simulation are given in Section 5. It is observed that the performances of the generalized class of estimators is remarkable.

摘要

当使用来自两个辅助变量（包括其分布函数）的信息时，我们建议在两阶段分层抽样下使用一类新的差分型估计量。偏差和 MSE 表达式导出至一级近似值。据观察，所提出的差分类型估计量比以下估计量更有效：样本均值、比率、指数比、传统差分类型、Chand、Singh 和 Choudhury、以及 Anieting 和 Ezugwu 回归类型。第 4 节进行了比较，第 5 节给出了基于真实数据集和模拟的结果。据观察，广义类估计器的性能非常显着。