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gamselBayes  

Bayesian Generalized Additive Model Selection
View on CRAN: Click here


Download and install gamselBayes package within the R console
Install from CRAN:
install.packages("gamselBayes")

Install from Github:
library("remotes")
install_github("cran/gamselBayes")

Install by package version:
library("remotes")
install_version("gamselBayes", "2.0-2")



Attach the package and use:
library("gamselBayes")
Maintained by
Matt P. Wand
[Scholar Profile | Author Map]
First Published: 2022-01-20
Latest Update: 2023-09-03
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 (2023) .
How to cite:
Matt P. Wand (2022). gamselBayes: Bayesian Generalized Additive Model Selection. R package version 2.0-2, https://cran.r-project.org/web/packages/gamselBayes. Accessed 05 Apr. 2025.
Previous versions and publish date:
1.0-1 (2022-01-20 09:42), 1.0-2 (2022-02-09 05:20), 1.0-3 (2023-04-12 06:40), 2.0-1 (2023-09-03 14:50)
Other packages that cited gamselBayes R package
View gamselBayes citation profile
Other R packages that gamselBayes depends, imports, suggests or enhances
Complete documentation for gamselBayes
Functions, R codes and Examples using the gamselBayes R package
Some associated functions: checkChains . effectTypes . effectTypesVector . gamselBayes.control . gamselBayes . gamselBayesUpdate . gamselBayesVignette . plot.gamselBayes . predict.gamselBayes . summary.gamselBayes . 
Some associated R codes: RcppExports.R .  Full gamselBayes package functions and examples
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