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arXiv 2609.27977stat.MEstat.CO

BFI:一个用于贝叶斯联邦推断的R包

BFI: An R Package for Bayesian Federated Inference

  • ARQ National Psychotrauma Center(ARQ国家心理创伤中心)

机构由 AI 辅助整理,请以论文原文为准。

Hassan Pazira

AI总结:

本文介绍R包BFI,实现贝叶斯联邦推断,支持多种回归模型,通过中心间交换参数摘要实现隐私保护下的多中心统计建模,并提供可复现工作流与合并分析对比。

AI中文摘要:

贝叶斯联邦推断(BFI)在个体水平观测数据无法跨中心合并时,从多中心数据估计统计模型。我们介绍了R包\pkg{BFI},该包实现了针对高斯、二项逻辑回归和生存回归模型的这一方法。每个中心执行贝叶斯最大后验分析,仅将参数估计和曲率信息发送至中心服务器,这些汇总信息在服务器上被合并以近似联合数据分析。该包支持先验设定、中心间异质性的结构化形式、多种参数化和灵活的生存分析基线风险模型,以及针对观察性和随机化研究的处理效应估计。我们描述了软件设计和中心间交换的信息,给出了这些分析的可复现工作流程,并将联邦结果与高斯、逻辑和生存模型的合并数据分析进行了比较。

英文摘要:

Bayesian Federated Inference (BFI) estimates statistical models from multicenter data when individual-level observations cannot be combined across centers. We present \pkg{BFI}, an \proglang{R} package that implements this methodology for Gaussian, binomial logistic, and survival regression models. Each center performs a Bayesian maximum a posteriori analysis and sends only parameter estimates and curvature information to a central server, where these summaries are combined to approximate the analysis of the combined data. The package supports prior specification, structured forms of between-center heterogeneity, several parametric and flexible baseline-hazard models for survival analysis, and treatment-effect estimation for observational and randomized studies. We describe the software design and the information exchanged between centers, give reproducible workflows for these analyses, and compare the federated results with pooled-data analyses for Gaussian, logistic, and survival models.

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