Package: dbnR
Type: Package
Title: Dynamic Bayesian Network Learning and Inference
Version: 0.8.0
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 three structure learning algorithms for dynamic Bayesian networks:
    Trabelsi G. (2013) <doi:10.1007/978-3-642-41398-8_34>, Santos F.P. and Maciel C.D. (2014)
    <doi:10.1109/BRC.2014.6880957>, Quesada D., Bielza C. and Larrañaga P. (2021)
    <doi:10.1007/978-3-030-86271-8_14>. It also offers the possibility to perform 
    forecasts of arbitrary length. A tool for visualizing the structure of the 
    net is also provided via the 'visNetwork' package. Further detailed information 
    and examples can be found in our Journal of Statistical Software paper 
    Quesada D., Larrañaga P. and Bielza C. (2025) <doi:10.18637/jss.v115.i06>.
Depends: R (>= 3.5.0), bnlearn (>= 4.5)
Imports: data.table (>= 1.12.4), Rcpp (>= 1.0.2), magrittr (>= 1.5), R6
        (>= 2.4.1), stats (>= 3.6.0), MASS (>= 7.3-55)
Suggests: visNetwork (>= 2.0.8), grDevices (>= 3.6.0), utils (>=
        3.6.0), graphics (>= 3.6.0), testthat (>= 2.1.0)
LinkingTo: Rcpp
URL: https://github.com/dkesada/dbnR
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.1
NeedsCompilation: yes
Packaged: 2026-01-13 14:00:14 UTC; Quesada
Author: David Quesada [aut, cre],
  Gabriel Valverde [ctb]
Maintainer: David Quesada <dkesada@gmail.com>
Repository: CRAN
Date/Publication: 2026-01-13 14:40:02 UTC
Built: R 4.6.0; x86_64-w64-mingw32; 2026-04-13 01:33:54 UTC; windows
Archs: x64
