在扩展的EWMA统计数据中,内存类型比率和产品估计器的组合适用于小麦生产
Rashiqa Zahid1, Muhammad Noor-Ul-Amin1, Imad Khan2
1COMSATS University Islamabad-Lahore Campus, Lahore, Pakistan.
Scientific reports
|August 20, 2023
概括
本研究引入了扩展指数加权移动平均 (EEWMA) 统计数据,以改进人口平均值估计. 通过结合过去和当前的数据,EEWMA统计提高了基于时间的调查中估计器的效率.
科学领域:
- 统计 统计 统计 统计
- 调查方法 调查方法
背景情况:
- 传统的估计器可能无法充分利用历史数据.
- 通过结合过去的观察,记忆类型统计提供了更高的效率.
研究的目的:
- 用扩展指数加权移动平均 (EEWMA) 统计数据来估计人口平均值.
- 为使用辅助变量进行基于时间的调查提出新的比率和产品估计器.
- 通过整合当前和过去的信息来提高估计者的效率.
主要方法:
- 这项研究使用了EEWMA统计,即内存类型统计.
- 比率和产品估计器是为基于时间的调查数据开发的.
- 估计的平均平方误差用于理论比较.
- 进行模拟研究以评估估计器的性能.
主要成果:
- 提出的基于EEWMA的估计器显示了效率的提高.
- 利用当前的样本和过去的信息都能显著提高估计器的性能.
- 数学比较证实了拟议估计者的优越性.
结论:
- 根据EEWMA的统计数据,在基于时间的调查中有效地改善了人口平均估计.
- 拟议的内存类型估计器通过利用历史数据提供了更有效的方法.
- 这些发现通过模拟研究和现实生活中的例子来验证.
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