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Updated: Jun 12, 2025

Sampling Soils in a Heterogeneous Research Plot
Published on: January 7, 2019
在分层随机抽样中采用两种辅助属性,在农业,人口,金融和教育领域应用的最佳估计方法
F A Almulhim1, Kanwal Iqbal2, Fathia M Al Samman3
1Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.
本研究引入了调查采样的最佳估计器,以提高使用辅助属性的人口平均估计. 这种新方法在数据分析中提供了更高的效率和准确性.
科学领域:
- 统计 统计 统计 统计
- 数据科学数据科学数据科学
- 调查方法 调查方法
背景情况:
- 大量的数据生成需要高效的分析方法.
- 传统的数据分析面临着资源限制 (时间,成本,劳动力).
- 调查采样对于有效估计人口参数至关重要.
研究的目的:
- 为人口参数开发一个改进的估计方法.
- 在分层随机抽样中为人口平均值提出一个最佳估计器.
- 为了利用两个辅助属性的信息进行增强的估计.
主要方法:
- 开发了分层随机采样的最佳估计器.
- 利用两个辅助属性来提高估计准确度.
- 预计偏差,平均平方误差 (MSE) 和建议估计器的最小MSE.
主要成果:
- 拟议的估计器在理论上优于现有方法.
- 在四种种群体上的实证评估表明了显著的效率增长.
- 获得的百分比相对效率 (PRE) 值为178.389,142.881,181.383和152.679.
结论:
- 建议的最佳估计器优于现有的估计器,用于估计人口平均值.
- 该方法为调查采样提供了更准确,更有效的方法.
- 数字示例证实了新估计器的实际适用性和增强性能.
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