Testing maximum entropy models with e-values

Francesca Giuffrida

doi:10.1103/xhf5-1l7p

2026-05-01

PRE

Francesca Giuffrida *

Diego Garlaschelli

Peter Grünwald

DOI：10.1103/xhf5-1l7p

原文链接

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摘要

En 中文

E值最近作为一种稳健且灵活的假设检验替代p值的方法出现，尤其是在可选续验下，即当收集来自进一步实验的额外数据时。在本工作中，我们定义了用于检验最大熵模型之间的最优E值，包括微正则（硬约束）和正则（软约束）两种设置。我们证明，当检验两个均为微正则假设时，所谓的增长率最优E变量具有精确的解析表达式，该表达式在正则情况下也作为有效的E变量。对于正则检验，由于通常无法获得精确解，我们引入了一种微正则近似，并通过理论论证和数值模拟验证了其优异的性能。然后，我们考虑受约束的二分类模型，重点关注2 × k列联表——这是统计学中的一个重要框架，也是复杂系统各种模型的自然表示。我们的微正则最优E变量在这两种情况下均表现良好，构成了一种即使在组数k随样本量增长这一挑战性情况下（如在用于分析真实世界异构网络和时间序列的具有增长特征的模型中）仍有效的工具。

Keyword:

EXPONENTIAL FAMILY

期刊

Physical Review E

IF:

2.4

论文数:

1.4K

被引数:

10.2W

机构

leiden university - excl lumc

学者数:

3.5W

论文数: 2.9W

被引数: 46

IMT School for Advanced Studies Lucca

学者数:

676

论文数: 701

被引数: 693

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