Package: ccdrAlgorithm
Title: CCDr Algorithm for Learning Sparse Gaussian Bayesian Networks
Version: 0.0.6
Date: 2022-04-10
Authors@R: c(
    person("Bryon", "Aragam", email = "sparsebn@gmail.com", role = c("aut", "cre")),
    person("Dacheng", "Zhang", role = c("aut"))
    )
Maintainer: Bryon Aragam <sparsebn@gmail.com>
Description: Implementation of the CCDr (Concave penalized Coordinate Descent with reparametrization) structure learning algorithm as described in Aragam and Zhou (2015) <https://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.
Depends: R (>= 3.2.3)
Imports: sparsebnUtils (>= 0.0.5), Rcpp (>= 0.11.0), stats, utils
LinkingTo: Rcpp
Suggests: testthat, graph, igraph, Matrix
URL: https://github.com/itsrainingdata/ccdrAlgorithm
BugReports: https://github.com/itsrainingdata/ccdrAlgorithm/issues
License: GPL (>= 2)
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2022-04-12 02:38:37 UTC; zigmund-3
Author: Bryon Aragam [aut, cre],
  Dacheng Zhang [aut]
Repository: CRAN
Date/Publication: 2022-04-12 02:52:30 UTC
