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

Implementation of the CCDr (Concave penalized Coordinate Descent with reparametrization) structure learning algorithm as described in Aragam and Zhou (2015) <http://www.jmlr.org/papers/v16/aragam15a.html>. This is a fast, score-based method for learning Bayesian networks that uses sparse regularization and block-cyclic coordinate descent.

Getting started

Package details

MaintainerBryon Aragam <[email protected]>
LicenseGPL (>= 2)
Version0.0.5
URL https://github.com/itsrainingdata/ccdrAlgorithm
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("itsrainingdata/ccdrAlgorithm")
itsrainingdata/ccdrAlgorithm documentation built on June 3, 2018, 1:13 p.m.