Abstract

The current investigation considers the query of assessment of estimators of population mean through calibration technique. We proposed new multi-variable calibrated estimator of mean in stratified sampling by employing the g multiple auxiliary variables. We introduce new variance function of the study variable in replacement to chi-square distance function under the assumption of known population variance of the study variable by some previous knowledge or past study as in case of Neyman allocation. It has been shown through simulation and numerical studies that the resultant estimators are much proficient than the usual combined mean estimator as well as combined ratio and regression estimators.

摘要

当前的调查考虑了通过校准技术评估总体均值估计量的问题。我们通过使用g多个辅助变量提出了分层抽样中新的多变量校准均值估计量。我们引入新的研究变量方差函数来替代卡方距离函数，假设研究变量的总体方差已知，通过一些先前的知识或过去的研究，如内曼分配的情况。通过模拟和数值研究表明，结果估计器比通常的组合均值估计器以及组合比率和回归估计器更熟练。