Package: EBEN 5.2

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 [aut, cre]

EBEN_5.2.tar.gz
EBEN_5.2.zip(r-4.7-x86_64)EBEN_5.2.zip(r-4.7-arm64)EBEN_5.2.zip(r-4.6-x86_64)EBEN_5.2.zip(r-4.6-arm64)
EBEN_5.2.tar.gz(r-4.7-arm64)EBEN_5.2.tar.gz(r-4.7-x86_64)EBEN_5.2.tar.gz(r-4.6-arm64)EBEN_5.2.tar.gz(r-4.6-x86_64)
EBEN_5.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
EBEN/json (API)

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

On CRAN:

Conda:

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

openblas

2.19 score 1 stars 31 scripts 439 downloads 1 mentions 11 exports 0 dependencies

Last updated from:6b80cd6d95. Checks:10 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK99
linux-devel-x86_64OK104
source / vignettesOK169
linux-release-arm64OK95
linux-release-x86_64OK120
windows-devel-arm64OK226
windows-devel-x86_64OK107
windows-release-arm64OK197
windows-release-x86_64OK74
wasm-releaseOK104

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

Dependencies: