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vagam: Variational Approximations for Generalized Additive Models

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>.

Version: 1.1
Depends: R (≥ 3.4.0), mgcv, gamm4, Matrix, mvtnorm, truncnorm
Published: 2019-12-06
DOI: 10.32614/CRAN.package.vagam
Author: Han Lin Shang ORCID iD [aut, cre, cph], Francis K.C. Hui ORCID iD [aut]
Maintainer: Han Lin Shang <hanlin.shang at anu.edu.au>
License: GPL-3
NeedsCompilation: no
Citation: vagam citation info
Materials: ChangeLog
CRAN checks: vagam results

Documentation:

Reference manual: vagam.pdf

Downloads:

Package source: vagam_1.1.tar.gz
Windows binaries: r-devel: vagam_1.1.zip, r-release: vagam_1.1.zip, r-oldrel: vagam_1.1.zip
macOS binaries: r-release (arm64): vagam_1.1.tgz, r-oldrel (arm64): vagam_1.1.tgz, r-release (x86_64): vagam_1.1.tgz, r-oldrel (x86_64): vagam_1.1.tgz
Old sources: vagam archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.