使用Ln型估计器来估计敏感研究变量的总体平均值,使用辅助信息
Muhammad Nouman Qureshi1, Yousaf Faizan2, Amrutha Shetty3
1School of Statistics, University of Minnesota, Twin Cities, USA.
Heliyon
|January 1, 2024
概括
本研究引入了两种新的ln型估计器,用于使用辅助信息进行敏感人群平均值估计. 这些估计器在统计分析中显示出更高的精度和准确性.
科学领域:
- 统计 统计 统计 统计
- 调查方法 调查方法
背景情况:
- 准确估计人口平均值至关重要,特别是对于敏感变量.
- 当辅助信息可用时,传统方法可能缺乏精度.
研究的目的:
- 为人口平均值估计提出两种新的In-type估计器.
- 在概率抽样中使用辅助信息来提高估计精度.
主要方法:
- 使用泰勒和日志序列扩展推导偏差和平均平方误差.
- 开发使用补充变量参数改进的估计器类.
- 与现有的平均值和比率估计器进行数学比较.
- 使用R软件对人工人群进行模拟研究.
- 现实数据的应用用于实际演示.
主要成果:
- 拟议的ln型估计器比传统估计器提供了更高的精度.
- 理论和模拟结果验证了新估计器的有效性.
- 在不同的人口结构中,估计器是强大的.
结论:
- 开发的ln型估计器为敏感变量提供了对人口平均值估计的更准确的方法.
- 使用辅助信息显著提高了估计效率.
- 该研究为处理敏感数据的调查统计学家提供了实用工具.
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