从图灵集和整数分区中得到的本福德定律
Alexander Kolpakov1, Aidan Rocke2
1Center for STEM, University of Austin, Austin, Texas 78758, USA.
Physical review. E
|November 18, 2025
概括
我们提出了两种模型来解释本福德的第一位数定律. 这些生成机制揭示了数据在特定约束下如何自然遵循对数分布,为数据模式提供了洞察力.
科学领域:
- 数据科学数据科学数据科学
- 统计分析 统计分析
- 计算数学 计算数学 计算数学
背景情况:
- 本福德定律描述了数字数据集中第一个数字的常见出现情况.
- 对本福德定律的现有解释是多样化的,有时缺乏统一的原则.
研究的目的:
- 开发新的生成机制,解释本福德的第一位数定律的出现.
- 阐明本福德定律在数据中普遍存在的条件和原因.
主要方法:
- 开发了一个概率化的图灵机 (PTM) 集合模型.
- 使用受约束分区 (爱因斯坦固体组合学) 建模.
- 进行数值实验以验证理论发现.
主要成果:
- 在PTM整体模型下,在最大化和停止长度约束下,产生本福德统计数据.
- 在Benford统计中观察到有关停止概率的阶段过渡.
- 约束分区模型重现了对数概况,澄清了非ergodicity 的作用.
结论:
- 两个互补的机制为本福德定律提供了全面的解释.
- 这些发现突出了,约束和数据分布之间的相互作用.
- 这项研究提供了一个强大的理论框架,用于理解第一位数现象.
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