NEWS.md

In itsrainingdata/ccdrAlgorithm: CCDr Algorithm for Learning Sparse Gaussian Bayesian Networks

ccdrAlgorithm 0.0.5

Notes

• Minor patch to fix failing CRAN check

ccdrAlgorithm 0.0.4

Features

• ccdr.run now supports black lists and white lists (sparsebn #6)
• Users can now use prior knowledge of variances via the new sigmas argument to ccdr.run (sparsebn #12)

Bug fixes

• ivn.rand = FALSE not handled correctly (#4)

ccdrAlgorithm 0.0.3

Features

• New generate_mvn_data() method to generate multivariate normal data from a DAG.

Notes

• Added warning when dataset contains more than 10,000 columns: This requires building from source. The CCDr algorithm has been safely tested on datasets with up to 8,000 variables.
• By default, ccdr.run() includes the node names in the sparsebnPath output.

ccdrAlgorithm 0.0.2

Features

• ccdr.run() is now compatible with interventional data

ccdrAlgorithm 0.0.1

• Initial stable release

itsrainingdata/ccdrAlgorithm documentation built on May 18, 2019, 7:12 a.m.