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 (2023) <doi:10.48550/arXiv.2201.00412>.
| Version: | 2.0-1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | Rcpp, methods |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | Ecdat |
| Published: | 2023-09-03 |
| DOI: | 10.32614/CRAN.package.gamselBayes |
| Author: | Virginia X. He 
[aut],
Matt P. Wand
[aut, cre] |
| Maintainer: | Matt P. Wand <matt.wand at uts.edu.au> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| CRAN checks: | gamselBayes results |
Documentation:
| Reference manual: | gamselBayes.pdf |
| Vignettes: |
gamselBayes User Manual |
Downloads:
| Package source: | gamselBayes_2.0-1.tar.gz |
| Windows binaries: | r-devel: gamselBayes_2.0-1.zip, r-release: gamselBayes_2.0-1.zip, r-oldrel: gamselBayes_2.0-1.zip |
| macOS binaries: | r-release (arm64): gamselBayes_2.0-1.tgz, r-oldrel (arm64): gamselBayes_2.0-1.tgz, r-release (x86_64): gamselBayes_2.0-1.tgz, r-oldrel (x86_64): gamselBayes_2.0-1.tgz |
| Old sources: | gamselBayes archive |
Linking:
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