dlbayes 0.1.0

Use Dirichlet Laplace Prior to Solve Linear Regression Problem and Do Variable Selection

Released Nov 14, 2018 by Shijia Zhang

This package can be loaded by Renjin but 4 out 5 tests failed.


glmnet 2.0-16 GIGrvg 0.5 expm 0.999-3 LaplacesDemon 16.1.1 MASS 7.3-51.1

The Dirichlet Laplace shrinkage prior in Bayesian linear regression and variable selection, featuring: utility functions in implementing Dirichlet-Laplace priors such as visualization; scalability in Bayesian linear regression; penalized credible regions for variable selection.



This package can be included as a dependency from a Java or Scala project by including the following your project's pom.xml file. Read more about embedding Renjin in JVM-based projects.

    <name>bedatadriven public repo</name>

View build log

Renjin CLI

If you're using Renjin from the command line, you load this library by invoking:


Test Results

This package was last tested against Renjin 0.9.2710 on Nov 16, 2018.



View GitHub Mirror

Release History