Tutorial on Bayesian Functional Regression Using Stan.

IF 1.8 4区医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY

Statistics in Medicine Pub Date : 2025-09-01 DOI:10.1002/sim.70265

Ziren Jiang, Ciprian Crainiceanu, Erjia Cui

引用次数: 0

Abstract

This manuscript provides step-by-step instructions for implementing Bayesian functional regression models using Stan. Extensive simulations indicate that the inferential performance of the methods is comparable to that of state-of-the-art frequentist approaches. However, Bayesian approaches allow for more flexible modeling and provide an alternative when frequentist methods are not available or may require additional development. Methods and software are illustrated using the accelerometry data from the National Health and Nutrition Examination Survey (NHANES).

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使用Stan的贝叶斯函数回归教程。

这份手稿提供了一步一步的说明实现贝叶斯函数回归模型使用Stan。大量的仿真表明，该方法的推理性能可与最先进的频率方法相媲美。然而，贝叶斯方法允许更灵活的建模，并在频率方法不可用或可能需要额外开发时提供一种替代方法。方法和软件的说明使用加速度计数据从国家健康和营养检查调查（NHANES）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Statistics in Medicine 医学-公共卫生、环境卫生与职业卫生

CiteScore

3.40

自引率

10.00%

发文量

334

审稿时长

2-4 weeks

期刊介绍： The journal aims to influence practice in medicine and its associated sciences through the publication of papers on statistical and other quantitative methods. Papers will explain new methods and demonstrate their application, preferably through a substantive, real, motivating example or a comprehensive evaluation based on an illustrative example. Alternatively, papers will report on case-studies where creative use or technical generalizations of established methodology is directed towards a substantive application. Reviews of, and tutorials on, general topics relevant to the application of statistics to medicine will also be published. The main criteria for publication are appropriateness of the statistical methods to a particular medical problem and clarity of exposition. Papers with primarily mathematical content will be excluded. The journal aims to enhance communication between statisticians, clinicians and medical researchers.