对于在线性回归中设定的水平的置信度集
Fang Wan1, Wei Liu2, Frank Bretz3
1Department of Mathematics and Statistics, Lancaster University, Bilrigg lane, Lancaster, LA1 4YF, UK.
Statistics in medicine
|January 6, 2024
概括
本研究引入了一种新的方法,用于在线性模型中构建回归水平集的置信集. 该方法广泛适用于各种参数回归模型,增强了统计分析.
科学领域:
- 统计 统计 统计 统计
- 统计建模 统计建模
背景情况:
- 传统的回归分析侧重于估计回归函数.
- 最近的重点转向估计设置的水平,定义为共变量值,回归函数超过一个值.
- 现有的研究主要涉及非参数回归和点估计.
研究的目的:
- 开发对线性回归分析中设定的水平的置信集.
- 将该方法扩展到其他参数回归模型.
主要方法:
- 构建正常误差线性回归的上,下和双边置信集.
- 使用同时的置信波段来构建置信集.
- 证明对通用线性模型,线性混合模型和通用线性混合模型的适用性.
主要成果:
- 对于线性回归水平集的置信集可以很容易地从同时的置信波段来构建.
- 拟议的构造方法广泛适用于具有单调链接函数的各种参数回归模型.
- 模拟研究和真实实例验证了该方法的有效性.
结论:
- 开发的方法提供了一个实用的方法,用于构建回归水平集的置信集.
- 该方法在不同参数模型中的广泛适用性为统计推理提供了显著的优势.
- 这项工作推进了回归水平集的估计,超出了点估计.
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