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vagam
View on CRAN: Click
here
Download and install vagam package within the R console
Install from CRAN:
install.packages("vagam")
Install from Github:
library("remotes")
install_github("cran/vagam")
Install by package version:
library("remotes")
install_version("vagam", "1.1")
Attach the package and use:
library("vagam")
Maintained by
Han Lin Shang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-01-09
Latest Update: 2019-12-06
Description:
Fits generalized additive models (GAMs) using a variational approximations (VA) framework. In brief, the VA framework provides a fully or at least closed to fully tractable lower bound approximation to the marginal likelihood of a GAM when it is parameterized as a mixed model (using penalized splines, say). In doing so, the VA framework aims offers both the stability and natural inference tools available in the mixed model approach to GAMs, while achieving computation times comparable to that of using the penalized likelihood approach to GAMs. See Hui et al. (2018) <doi:10.1080/01621459.2018.1518235>.
How to cite:
Han Lin Shang (2019). vagam: Variational Approximations for Generalized Additive Models. R package version 1.1, https://cran.r-project.org/web/packages/vagam. Accessed 07 Nov. 2024.
Previous versions and publish date:
1.0 (2019-01-09 18:00)
Other packages that cited vagam R package
View vagam citation profile
Other R packages that vagam depends,
imports, suggests or enhances
Complete documentation for vagam
Functions, R codes and Examples using
the vagam R package
Some associated functions: gamsim . plot.vagam . predict.vagam . summary.vagam . vagam-package . vagam . wage_data .
Some associated R codes: calc.VAlogL.R . gamsim.R . info.valouis_internal.R . plot.vagam.R . predict.vagam.R . print.vagam.R . ridge.iwls_internal.R . simrun_binomial_internal.R . simrun_normal_internal.R . simrun_poisson_internal.R . summary.vagam.R . vagam.R . Full vagam package functions and examples
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