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一个改进的估计器类,用于估计人口分布函数在分层随机抽样下
Sohaib Ahmad1, Javid Shabbir2, Walid Emam3
1Department of Statistics, Abdul Wali Khan University, Mardan, Pakistan.
本研究引入了使用分层采样中的辅助数据对人口分布函数 (DF) 进行改进的日志比率指数估计器. 与现有方法相比,这些新估计器显示出更高的效率和更低的平均平方误差 (MSE).
科学领域:
- 统计 统计 统计 统计
- 调查方法 调查方法
背景情况:
- 在统计分析中,对人口分布函数 (DF) 的准确估计至关重要.
- 分层随机抽样是一种常见的技术,用于提高调查的精度.
- 辅助信息可以提高估计器的效率.
研究的目的:
- 为人口DF提出一个增强的日志比率指数类型估计器家族.
- 评估这些新估计器与现有估计器的性能.
- 在分层随机抽样框架内利用辅助信息.
主要方法:
- 发展一个泛化的类型的日志比率指数估计器.
- 偏差和平均平方误差 (MSE) 表达式的近似值为第一顺序.
- 使用实际和模拟数据集进行绩效评估.
主要成果:
- 对于DF的拟议估计器显示出比初步估计器更好的性能.
- 与其他检查的估计器相比,增强估计器显示了更高的效率.
- 观察到效率的显著提高,表明在MSE方面,拟议的估计器的优越性.
结论:
- 建议的日志比率指数估计器为估计人口分布函数提供了显著的改进.
- 在分层采样中使用辅助信息可以提高估计效率.
- 提出的估计器优于现有方法,特别是在最小化MSE方面.
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