Package: vagam 1.1

Han Lin Shang

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>.

Authors:Han Lin Shang [aut, cre, cph], Francis K.C. Hui [aut]

vagam_1.1.tar.gz
vagam_1.1.tar.gz(r-4.5-noble)vagam_1.1.tar.gz(r-4.4-noble)
vagam_1.1.tgz(r-4.4-emscripten)vagam_1.1.tgz(r-4.3-emscripten)
vagam.pdf |vagam.html✨
vagam/json (API)

# Install 'vagam' in R:
install.packages('vagam', repos = 'https://cloud.r-project.org')
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 136 downloads 4 exports 17 dependencies

Last updated 5 years agofrom:cedb18bba4. Checks:1 OK, 2 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 04 2025
R-4.5-linuxNOTEMar 04 2025
R-4.4-linuxNOTEMar 04 2025

Exports:gamsimplot.vagampredict.vagamvagam

Dependencies:bootgamm4latticelme4MASSMatrixmgcvminqamvtnormnlmenloptrrbibutilsRcppRcppEigenRdpackreformulastruncnorm

Citation

To cite the vagam package, use:

Shang HL, Hui FK (2019). vagam: Variational Approximations for Generalized Additive Models. R package version 1.1, https://CRAN.R-project.org/package=vagam.

Hui FKC, You C, Shang HL, Mueller S (2019). “Semiparametric regression using variational approximations.” Journal of the American Statistical Association. https://arxiv.org/abs/1810.01949.

Corresponding BibTeX entries: 

  @Manual{,
    title = {{vagam}: Variational Approximations for Generalized
      Additive Models},
    author = {Han Lin Shang and Francis K.C. Hui},
    year = {2019},
    note = {R package version 1.1},
    url = {https://CRAN.R-project.org/package=vagam},
  }

  @Article{,
    title = {Semiparametric regression using variational
      approximations},
    author = {F. K. C. Hui and C. You and H. L. Shang and S. Mueller},
    journal = {Journal of the American Statistical Association},
    year = {2019},
    url = {https://arxiv.org/abs/1810.01949},
  }