Kumar Anoop, Bhushan Shashi, Pokhrel Rohini, Emam Walid, Tashkandy Yusra, Khan M J S
Department of Statistics, Central University of Haryana, Mahendergarh, 123031, India.
Department of Statistics, University of Lucknow, Lucknow, 226007, India.
Heliyon. 2024 Jul 4;10(14):e33839. doi: 10.1016/j.heliyon.2024.e33839. eCollection 2024 Jul 30.
This article considers the issue of domain mean estimation utilizing bivariate auxiliary information based enhanced direct and synthetic logarithmic type estimators under simple random sampling (SRS). The expressions of mean square error (MSE) of the proposed estimators are provided to the order approximation. The efficiency criteria are derived to exhibit the dominance of the proposed estimators. To exemplify the theoretical results, a simulation study is conducted on a hypothetically drawn trivariate normal population from programming language. Some applications of the suggested methods are also provided by analyzing the actual data from the municipalities of Sweden and acreage of paddy crop in the Mohanlal Ganj tehsil of the Indian state of Uttar Pradesh. The findings of the simulation and real data application exhibit that the proposed direct and synthetic logarithmic estimators dominate the conventional direct and synthetic mean, ratio, and logarithmic estimators in terms of least MSE and highest percent relative efficiency.
本文考虑了在简单随机抽样（SRS）下，利用基于双变量辅助信息的增强型直接和合成对数型估计量来估计总体均值的问题。给出了所提估计量的均方误差（MSE）表达式至近似阶数。推导了效率准则以展示所提估计量的优势。为举例说明理论结果，使用编程语言对假设抽取的三变量正态总体进行了模拟研究。通过分析瑞典各市镇的实际数据以及印度北方邦莫汉拉尔甘杰乡的水稻种植面积，还给出了所建议方法的一些应用。模拟和实际数据应用的结果表明，所提直接和合成对数估计量在最小均方误差和最高相对效率百分比方面优于传统的直接和合成均值、比率以及对数估计量。
