BayesReg Ver 1.4: High-Dimensional Bayesian Regularised Regression, now with grouping of variables

Version 1.4 of the BayesReg package has been released. This has a large additional feature — users can now assign predictors to logical groupings (potentially overlapping, so predictors can be part of multiple groups). This can be used to exploit a priori knowledge regarding predictors and how they may be related to each other (for example, in grouping genetic data into genes and collections of genes such as pathways). The features added are:

  1. Added option ‘groups’ which allows grouping of variables into potentially overlapping groups
  2. Grouping works with HS, HS+ and lasso priors
  3. Fixed a regression bug with g priors and logistic models
  4. Updated examples to demonstrate grouping

You can obtain the latest version of the BayesReg software fromĀ here.

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