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Efficient algorithms for fitting the regularization path of linear regression, GLM, and Cox regression models with grouped penalties. This includes group selection methods such as group lasso, group MCP, and group SCAD as well as bi-level selection methods such as the group exponential lasso, the composite MCP, and the group bridge.

copied from cf-staging / r-grpreg

Installers

Info: This package contains files in non-standard labels.
  • linux-64 v3.5.0
  • osx-64 v3.5.0
  • win-64 v3.5.0

conda install

To install this package run one of the following:
conda install conda-forge::r-grpreg
conda install conda-forge/label/cf201901::r-grpreg
conda install conda-forge/label/cf202003::r-grpreg
conda install conda-forge/label/gcc7::r-grpreg

Description


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