ReMoDe - 在顺序数据分布中的递归模式检测.
Madlen Hoffstadt1, Lourens Waldorp1, Javier Garcia-Bernardo2
1Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.
The British journal of mathematical and statistical psychology
|February 19, 2026
概括
我们介绍了ReMoDe,这是一种用于顺序数据的新递归模式检测方法. ReMoDe准确地识别了分布中的模式,在模拟中表现优于现有的方法.
科学领域:
- 统计 统计 统计 统计
- 数据分析 数据分析
背景情况:
- 在顺序数据中检测模式对于心理学和医学等学科至关重要.
- 现有的模式检测方法往往是描述性的或不适合顺序数据.
研究的目的:
- 为单变序分布提出一种新的递归模态检测方法 (ReMoDe).
- 解决当前方法的局限性,当应用到顺序尺度时.
主要方法:
- 开发了一种用于模式检测的递归显著性测试方法.
- 进行了一项基准研究,使用了不同大小的172个模拟顺序数据集.
- 执行稳定性测试并计算p值和贝叶斯因子,用于检测到的模式.
主要成果:
- 在模拟中,ReMoDe与已建立的模式检测方法相比,表现优越.
- 该方法为检测到的模式提供统计措施 (p值,贝叶斯因子).
- 开源的R和Python软件包可用于简单的实现.
结论:
- ReMoDe提供了一个强大而准确的解决方案,用于在顺序数据中检测模式.
- 该方法增强了分布的分析,帮助研究人员识别诸如两极分化或发病率群等模式.
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