On Enhanced Ratio-Type Estimators Using Quantile Regression for Finite Population Mean under Robustness and Empirical Validation

IF 1.4 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES
Muhammad Zohaib, Waqas Latif, Mubeen Alam
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引用次数: 0

Abstract

When the conditions of traditional regression analysis aren't met, an alternative method called quantile regression is utilized to estimate the value of the study variable across different quantiles of the distribution. This study proposes leveraging quantile regression information to develop ratio-type estimators for the finite population mean, particularly under robust measures of auxiliary variables in simple random sampling (SRS) without replacement. The performance of these proposed families of estimators is compared with existing studies using metrics such as mean squared error (MSE) equations and percentage relative efficiency (PRE). Additionally, this article incorporates simulation studies. Moreover, various real-world datasets are considered for empirical investigation to validate the theoretical findings.

基于稳健性和经验验证的有限总体均值分位数回归的增强比率型估计
当传统回归分析的条件不满足时,采用一种称为分位数回归的替代方法来估计研究变量在分布的不同分位数上的值。本研究建议利用分位数回归信息来开发有限总体均值的比率型估计,特别是在简单随机抽样(SRS)中辅助变量的鲁棒测量下,而无需替换。利用均方误差(MSE)方程和相对效率百分比(PRE)等指标,将这些估计器家族的性能与现有研究进行了比较。此外,本文还结合了仿真研究。此外,还考虑了各种现实世界的数据集进行实证调查,以验证理论发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.00
自引率
5.90%
发文量
122
审稿时长
>12 weeks
期刊介绍: The aim of this journal is to foster the growth of scientific research among Iranian scientists and to provide a medium which brings the fruits of their research to the attention of the world’s scientific community. The journal publishes original research findings – which may be theoretical, experimental or both - reviews, techniques, and comments spanning all subjects in the field of basic sciences, including Physics, Chemistry, Mathematics, Statistics, Biology and Earth Sciences
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