Package: EBEN 5.1

Anhui Huang

EBEN: Empirical Bayesian Elastic Net

Provides the Empirical Bayesian Elastic Net for handling multicollinearity in generalized linear regression models. As a special case of the 'EBglmnet' package (also available on CRAN), this package encourages a grouping effects to select relevant variables and estimate the corresponding non-zero effects.

Authors:Anhui Huang

EBEN_5.1.tar.gz
EBEN_5.1.tar.gz(r-4.5-noble)EBEN_5.1.tar.gz(r-4.4-noble)
EBEN_5.1.tgz(r-4.4-emscripten)EBEN_5.1.tgz(r-4.3-emscripten)
EBEN.pdf |EBEN.html✨
EBEN/json (API)

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

Peer review:

Uses libs:
  • openblas– Optimized BLAS
Datasets:
  • BASIS - An Example Data File for the Gauss Model
  • BASISbinomial - An Example Data File for the Binomial Model
  • y - Sample Response Data for Gaussian Model
  • yBinomial - Sample Variable Data for Binomial Model

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

11 exports 0.23 score 0 dependencies 1 mentions 30 scripts 323 downloads

Last updated 1 years agofrom:a43e993c25. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 26 2024
R-4.5-linux-x86_64OKAug 26 2024

Exports:CVonePairEBelasticNet.BinomialEBelasticNet.BinomialCVEBelasticNet.GaussianEBelasticNet.GaussianCVEBlassoNEG.BinomialEBlassoNEG.BinomialCVEBlassoNEG.GaussianEBlassoNEG.GaussianCVijIndexlambdaMax

Dependencies: