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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>.

Version:2.0-3
Depends:R (≥ 3.5.0)
Imports:Rcpp, methods
LinkingTo:Rcpp,RcppArmadillo
Suggests:Ecdat
Published:2025-05-01
DOI:10.32614/CRAN.package.gamselBayes
Author:Virginia X. HeORCID iD [aut], Matt P. WandORCID iD [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.html ,gamselBayes.pdf
Vignettes:gamselBayes User Manual (source)

Downloads:

Package source: gamselBayes_2.0-3.tar.gz
Windows binaries: r-devel:gamselBayes_2.0-3.zip, r-release:gamselBayes_2.0-3.zip, r-oldrel:gamselBayes_2.0-3.zip
macOS binaries: r-release (arm64):gamselBayes_2.0-3.tgz, r-oldrel (arm64):gamselBayes_2.0-3.tgz, r-release (x86_64):gamselBayes_2.0-3.tgz, r-oldrel (x86_64):gamselBayes_2.0-3.tgz
Old sources: gamselBayes archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=gamselBayesto link to this page.


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