Modified Exponential Ratio-Type Estimator of Population Mean in Stratified Sampling using Calibration Approach

Q3 Mathematics
None Neha Garg, None Housila P. Singh, None Menakshi Pachori
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引用次数: 0

Abstract

In this paper, the problem of estimation of finite population mean in stratified random sampling is considered. Two improved exponential logarithmic type calibration estimators for finite population mean have been proposed for stratified random sampling when auxiliary information related to variable under study is available for each stratum. To judge the performance of the proposed estimators, a simulation study has been carried out in R-software using two datasets, one real and another one artificial generated population. The proposed estimators have also been compared with the estimators developed by Bahl and Tuteja [1] and Singh [17] in case of stratified random sampling.
用校正方法估计分层抽样总体均值的修正指数比率型估计
研究了分层随机抽样中有限总体均值的估计问题。提出了两种改进的指数对数型有限总体均值校正估计方法,用于分层随机抽样中各层均可获得与研究变量相关的辅助信息。为了判断所提出的估计器的性能,在r软件中使用两个数据集进行了模拟研究,一个是真实的,另一个是人工生成的人口。在分层随机抽样的情况下,还将所提出的估计量与Bahl和Tuteja[1]和Singh[17]开发的估计量进行了比较。
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来源期刊
CiteScore
0.50
自引率
0.00%
发文量
5
期刊介绍: The Journal of Modern Applied Statistical Methods is an independent, peer-reviewed, open access journal designed to provide an outlet for the scholarly works of applied nonparametric or parametric statisticians, data analysts, researchers, classical or modern psychometricians, and quantitative or qualitative methodologists/evaluators.
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