Package: sparsebn
Title: Learning Sparse Bayesian Networks from High-Dimensional Data
Version: 0.0.4
Date: 2017-03-14
Authors@R: person("Bryon", "Aragam", email = "sparsebn@gmail.com", role = c("aut", "cre"))
Maintainer: Bryon Aragam <sparsebn@gmail.com>
Description: Fast methods for learning sparse Bayesian networks from high-dimensional data using sparse regularization, as described in as described in Aragam, Gu, and Zhou (2017) <https://arxiv.org/abs/1703.04025>. Designed to handle mixed experimental and observational data with thousands of variables with either continuous or discrete observations.
Depends: R (>= 3.2.3), sparsebnUtils (>= 0.0.4), ccdrAlgorithm (>=
        0.0.3), discretecdAlgorithm (>= 0.0.3)
Suggests: knitr, rmarkdown, mvtnorm, igraph, graph, testthat
URL: https://github.com/itsrainingdata/sparsebn
BugReports: https://github.com/itsrainingdata/sparsebn/issues
License: GPL (>= 2)
RoxygenNote: 6.0.1
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2017-03-15 16:50:34 UTC; Zigmund-2
Author: Bryon Aragam [aut, cre]
Repository: CRAN
Date/Publication: 2017-03-16 01:08:03
Built: R 3.2.5; ; 2017-04-20 09:03:19 UTC; windows
