Ahmad Sohaib, Shabbir Javid, Emam Walid, Zahid Erum, Aamir Muhammad, Khalid Mohd, Muhammad Anas Malik
Department of Statistics, Abdul Wali Khan University, Mardan, Pakistan.
Department of Statistics, University of Wah, Wah Cantt, Pakistan.
Heliyon. 2024 Mar 22;10(7):e28272. doi: 10.1016/j.heliyon.2024.e28272. eCollection 2024 Apr 15.
The main objective of the current study is to suggest an enhanced family of log ratio-exponential type estimators for population distribution function (DF) using auxiliary information under stratified random sampling. Putting different choices in our suggested generalized class of estimators, we found some Specific estimators. The bias and MSE expressions of the estimators have been approximated up to the first order. By using the actual and simulated data sets, we measured the performance of estimators. Based on the results, the suggested estimators for DF show better performance as compared to the preliminary estimators considered here. The suggested estimators have a advanced efficiency than the other estimators examined with the estimators , and for both the actual and simulated data sets. The magnitude of the improvement in efficiency is noteworthy, indicating the superiority of the proposed estimators in terms of MSE.
本研究的主要目的是提出一类在分层随机抽样下利用辅助信息的、用于总体分布函数（DF）的增强型对数比率指数型估计量族。在我们建议的广义估计量类中进行不同选择，我们得到了一些特定的估计量。这些估计量的偏差和均方误差表达式已近似到一阶。通过使用实际数据集和模拟数据集，我们衡量了估计量的性能。基于结果，与这里考虑的初步估计量相比，建议的DF估计量表现出更好的性能。对于实际数据集和模拟数据集，建议的估计量比用估计量 、 检验的其他估计量具有更高的效率。效率提高的幅度值得注意，表明所提出的估计量在均方误差方面具有优越性。
