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 (2021) <arXiv:2201.00412>.
||R (≥ 3.5.0)
||Virginia X. He [aut],
Matt P. Wand
||Matt P. Wand <matt.wand at uts.edu.au>
||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Please use the canonical form
to link to this page.