Tutorial on Bayesian Functional Regression Using Stan

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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Journal
Statistics in Medicine
Published
2025-09-01
DOI
https://doi.org/10.1002/sim.70265
Primary Topic
Statistical Methods and Inference
Type
article
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article

Tutorial on Bayesian Functional Regression Using Stan

Ziren Jiang, Erjia Cui, Ciprian M. Crainiceanu
Statistics in Medicine
Statistical Methods and Inference
article

Tutorial on Bayesian Functional Regression Using Stan

Ziren Jiang, Erjia Cui, Ciprian M. Crainiceanu
article en

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).

Statistics in MedicineVol. 44(20-22)
University of Minnesota (US), Johns Hopkins University (US)
Openalex Percentile: Top 77%
Statistical Methods and Inference
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