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Bayesian Clustering Factor Models

delete2026-01-01
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OA
AI
H
Hwasoo Shin
M
Marco A. R. Ferreira
A
Allison N. Tegge *
DOI：10.1002/sim.70350delete
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摘要

摘要

En 中文
我们提出了一种用于同时降维和聚类的全新框架。该框架基于一类新颖的贝叶斯聚类因子模型。这些模型假设因子模型结构，其中公共因子向量遵循高斯分布的混合分布。我们开发了一种Gibbs采样器来探索后验分布，并提出了一个信息准则以选择聚类数量和因子数量。模拟研究显示，我们的推断方法能够恰当量化不确定性。此外，与两种先前发表的竞争方法相比，我们的信息准则在正确选择聚类数量和因子数量方面表现更优。最后，我们通过将框架应用于阿片类药物使用障碍康复数据的应用实例，展示了其能力，其中个体聚类可能有助于个性化医疗保健。
Keyword:
Bayesian factors models
clustering methods
mixtures of Gaussian distributions
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期刊

S
Statistics in Medicine
IF:
1.8
论文数:
315
被引数:
3.4W

机构

V
virginia polytechnic institute & state university
学者数:
1.2K
论文数: 523
被引数: 0
H
Henry Ford Health System
学者数:
9.2K
论文数: 7.4K
被引数: 3.4K
引用论文

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