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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.0-3 |
rolling source/ R- | gamselBayes_2.0-3.tar.gz |
1.7 MiB |
2.0-3 |
rolling linux/jammy R-4.5 | gamselBayes_2.0-3.tar.gz |
936.1 KiB |
2.0-3 |
latest source/ R- | gamselBayes_2.0-3.tar.gz |
1.7 MiB |
2.0-3 |
latest linux/jammy R-4.5 | gamselBayes_2.0-3.tar.gz |
936.1 KiB |
2.0-3 |
2026-04-23 source/ R- | gamselBayes_2.0-3.tar.gz |
1.7 MiB |
2.0-3 |
2026-04-09 windows/windows R-4.5 | gamselBayes_2.0-3.zip |
1.2 MiB |
2.0-2 |
2025-04-20 source/ R- | gamselBayes_2.0-2.tar.gz |
1.7 MiB |