在两阶段采样下使用GWR辅助的有限人口总数综合估计器:一个模型辅助的方法
Nobin Chandra Paul1,2,3, Anil Rai4, Tauqueer Ahmad1
1ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India.
Journal of applied statistics
|September 13, 2024
概括
本研究引入了一种新的地理加权回归 (GWR) 模型辅助估计器,用于调查采样. 这种先进的方法通过结合空间信息来改进有限人口总估计,优于传统技术.
科学领域:
- 调查抽样调查抽样
- 空间统计的空间统计.
- 统计建模 统计建模
背景情况:
- 辅助信息在调查采样中增强了有限人口参数估计.
- 现有的方法提供了在估计过程中整合辅助数据的实用方法.
- 空间非静止性可能会影响传统估计器的准确性.
研究的目的:
- 为有限人口总数提出一个新的地理加权回归 (GWR) 模型辅助的综合估计器.
- 在两阶段采样设计中评估拟议估计器的性能.
- 为了证明空间信息在调查采样中的实用性.
主要方法:
- 开发一个GWR模型辅助的综合估计器.
- 在两阶段抽样框架内应用.
- 使用空间模拟研究进行实证评估.
主要成果:
- 拟议的GWR估计器在空间非静止存在的情况下显著优于现有的估计器 (双相HT,比率,回归).
- 空间模拟研究验证了GWR辅助估计器的统计特性和优势.
- 这些发现强调了空间信息在提高估计精度方面的关键作用.
结论:
- 在存在空间效应时,GWR模型辅助的综合估计器为调查采样提供了一个强大的方法.
- 通过GWR纳入空间信息可以提高有限人口总估计的准确性.
- 这项研究强调了空间考虑在现代调查方法学的重要性.
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