Package: dbnR
Type: Package
Title: Dynamic Bayesian Network Learning and Inference
Version: 0.5.3
Authors@R: c(
    person("David", "Quesada", email = "dkesada@gmail.com", role = c("aut", "cre")),
    person("Gabriel", "Valverde", email = "gabrielvalverdecastilla@gmail.com", role = "ctb"))
Description: Learning and inference over dynamic Bayesian networks of arbitrary 
    Markovian order. Extends some of the functionality offered by the 'bnlearn' 
    package to learn the networks from data and perform exact inference. 
    It offers two structure learning algorithms for dynamic Bayesian networks
    and the possibility to perform forecasts of arbitrary length. A tool for 
    visualizing the structure of the net is also provided via the 'visNetwork' 
    package.
Depends: R (>= 3.5.0)
Imports: bnlearn (>= 4.5), data.table (>= 1.12.4), Rcpp (>= 1.0.2),
        magrittr (>= 1.5), R6 (>= 2.4.1)
Suggests: visNetwork (>= 2.0.8), grDevices (>= 3.6.0), utils (>=
        3.6.0), graphics (>= 3.6.0), stats (>= 3.6.0), testthat (>=
        2.1.0)
LinkingTo: Rcpp
URL: https://github.com/dkesada/dbnR
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-10-13 08:20:25 UTC; Quesada
Author: David Quesada [aut, cre],
  Gabriel Valverde [ctb]
Maintainer: David Quesada <dkesada@gmail.com>
Repository: CRAN
Date/Publication: 2020-10-13 08:40:05 UTC
Built: R 3.6.2; x86_64-apple-darwin15.6.0; 2020-10-14 11:33:55 UTC; unix
Archs: dbnR.so.dSYM
