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DESCRIPTION
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DESCRIPTION
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Package: ccdrAlgorithm
Title: CCDr Algorithm for Learning Sparse Gaussian Bayesian Networks
Version: 0.0.5
Date: 2018-06-01
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) <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.
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: 6.0.1