sparsebn (0.1.0)
Learning Sparse Bayesian Networks from High-Dimensional Data.
https://github.com/itsrainingdata/sparsebn
http://cran.r-project.org/web/packages/sparsebn
Fast methods for learning sparse Bayesian networks from high-dimensional data using sparse regularization, as described in Aragam, Gu, and Zhou (2017) . Designed to handle mixed experimental and observational data with thousands of variables with either continuous or discrete observations.
Maintainer:
Bryon Aragam
Author(s): Bryon Aragam [aut, cre], Jiaying Gu [aut], Dacheng Zhang [aut], Qing Zhou [aut]
License: GPL (>= 2)
Uses: ccdrAlgorithm, discretecdAlgorithm, sparsebnUtils, graph, igraph, mvtnorm, testthat, knitr, rmarkdown
Released about 1 month ago.
