Package: gamselBayes
Version: 2.0-3
Date: 2025-05-01
Title: Bayesian Generalized Additive Model Selection
Authors@R: c(person("Virginia X.", "He", role = "aut",
                    email = "virginia.x.he@student.uts.edu.au",
                    comment = c(ORCID = "0000-0002-0238-5018")),
             person("Matt P.", "Wand", role = c("aut","cre"),
                    email = "matt.wand@uts.edu.au",
                    comment = c(ORCID = "0000-0003-2555-896X")))
Maintainer: Matt P. Wand <matt.wand@uts.edu.au>
Description: 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>. 
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Imports: Rcpp, methods
Suggests: Ecdat
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2025-05-01 06:24:45 UTC; mwand
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>)
Repository: CRAN
Date/Publication: 2025-05-01 07:40:02 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-26 18:43:38 UTC; unix
Archs: gamselBayes.so.dSYM
