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gamselBayes: Bayesian Generalized Additive Model Selection
Generalized additive model selection via approximate Bayesian inference is provided. Bayesian mixed model-based penalized splines with spike-and-slab-type coefficient prior distributions are used to facilitate fitting and selection. The approximate Bayesian inference engine options are: (1) Markov chain Monte Carlo and (2) mean field variational Bayes. Markov chain Monte Carlo has better Bayesian inferential accuracy, but requires a longer run-time. Mean field variational Bayes is faster, but less accurate. The methodology is described in He and Wand (2024) <doi:10.1007/s10182-023-00490-y>.
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Package details |
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| Author | Virginia X. He [aut] (ORCID: <https://orcid.org/0000-0002-0238-5018>), Matt P. Wand [aut, cre] (ORCID: <https://orcid.org/0000-0003-2555-896X>) |
| Maintainer | Matt P. Wand <matt.wand@uts.edu.au> |
| License | GPL (>= 2) |
| Version | 2.0-3 |
| Package repository | View on CRAN |
| Installation |
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