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Efficient algorithm for solving ultra-sparse regularized regression models using a variational Bayes algorithm with a spike (l0) prior. Algorithm is solved on a path, with coordinate updates, and is capable of generating very sparse models. There are very general model diagnostics for controling type-1 error included in this package.

Installers

  • linux-64 v0.0.5
  • osx-64 v0.0.5
  • win-64 v0.0.5

conda install

To install this package run one of the following:
conda install r_test::r-vbsr

Description


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