Tutorial on Bayesian Functional Regression Using Stan
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866918356945207296 |
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| author | Jiang, Ziren Crainiceanu, Ciprian Cui, Erjia |
| author_facet | Jiang, Ziren Crainiceanu, Ciprian Cui, Erjia |
| contents | 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). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_05633 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Tutorial on Bayesian Functional Regression Using Stan Jiang, Ziren Crainiceanu, Ciprian Cui, Erjia Methodology Computation 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). |
| title | Tutorial on Bayesian Functional Regression Using Stan |
| topic | Methodology Computation |
| url | https://arxiv.org/abs/2505.05633 |