Package: glinternet 1.0.12

glinternet: Learning Interactions via Hierarchical Group-Lasso Regularization

Group-Lasso INTERaction-NET. Fits linear pairwise-interaction models that satisfy strong hierarchy: if an interaction coefficient is estimated to be nonzero, then its two associated main effects also have nonzero estimated coefficients. Accommodates categorical variables (factors) with arbitrary numbers of levels, continuous variables, and combinations thereof. Implements the machinery described in the paper "Learning interactions via hierarchical group-lasso regularization" (JCGS 2015, Volume 24, Issue 3). Michael Lim & Trevor Hastie (2015) <doi:10.1080/10618600.2014.938812>.

Authors:Michael Lim, Trevor Hastie

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glinternet.pdf |glinternet.html
glinternet/json (API)

# Install 'glinternet' in R:
install.packages('glinternet', repos = c('https://michael626.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

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

4.16 score 12 stars 2 packages 39 scripts 1.0k downloads 5 mentions 2 exports 0 dependencies

Last updated 3 years agofrom:67a32a33d0. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 01 2024
R-4.5-win-x86_64OKNov 01 2024
R-4.5-linux-x86_64OKNov 01 2024
R-4.4-win-x86_64OKNov 01 2024
R-4.4-mac-x86_64OKNov 01 2024
R-4.4-mac-aarch64OKNov 01 2024
R-4.3-win-x86_64OKNov 01 2024
R-4.3-mac-x86_64OKNov 01 2024
R-4.3-mac-aarch64OKNov 01 2024

Exports:glinternetglinternet.cv

Dependencies: