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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "bnlearn" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'bnlearn: Bayesian Network Structure Learning, Parameter Learning and Inference'
version: 5.2.1
identifiers:
- type: doi
  value: 10.32614/CRAN.package.bnlearn
abstract: Bayesian network structure learning, parameter learning and inference. This
  package implements constraint-based (PC, GS, IAMB, Inter-IAMB, MMPC, Hiton-PC, HPC),
  pairwise (ARACNE and Chow-Liu), score-based (Hill-Climbing, Tabu Search, DirectLiNGAM)
  and hybrid (MMHC, RSMAX2, H2PC) structure learning algorithms for discrete, Gaussian,
  conditional Gaussian and zero-inflated networks, along with many score functions
  and conditional independence tests. The Naive Bayes and the Tree-Augmented Naive
  Bayes (TAN) classifiers are also implemented. Some utility functions (model comparison
  and manipulation, random data generation, arc orientation testing, simple and advanced
  plots) are included, as well as support for parameter estimation (maximum likelihood
  and Bayesian) and inference, conditional probability queries, interventions, counterfactuals,
  cross-validation, bootstrap and model averaging. Development snapshots with the
  latest bugfixes are available from <https://www.bnlearn.com/>.
authors:
- family-names: Scutari
  given-names: Marco
  email: scutari@bnlearn.com
preferred-citation:
  type: book
  title: Bayesian Networks with Examples in R
  authors:
  - family-names: Scutari
    given-names: Marco
    email: scutari@bnlearn.com
  - family-names: Denis
    given-names: Jean-Baptiste
  edition: 2nd
  publisher:
    name: Chapman and Hall
    address: Boca Raton
  year: '2021'
  notes: ISBN 978-0367366513
repository: https://scutari.r-universe.dev
commit: 7d44622a52c29c2d666a8661d048e2b5709a7944
url: https://www.bnlearn.com/
date-released: '2026-07-17'
contact:
- family-names: Scutari
  given-names: Marco
  email: scutari@bnlearn.com
references:
- type: book
  title: Bayesian Networks in R with Applications in Systems Biology
  authors:
  - family-names: Nagarajan
    given-names: Radhakrishnan
  - family-names: Scutari
    given-names: Marco
  publisher:
    name: Springer
    address: New York
  year: '2013'
  notes: ISBN 978-1-4614-6445-7, 978-1-4614-6446-4
  doi: 10.1007/978-1-4614-6446-4
- type: article
  title: 'Bayesian Network Constraint-Based Structure Learning Algorithms: Parallel
    and Optimized Implementations in the bnlearn R Package'
  authors:
  - family-names: Scutari
    given-names: Marco
    email: scutari@stats.ox.ac.uk
  journal: Journal of Statistical Software
  year: '2017'
  volume: '77'
  issue: '2'
  doi: 10.18637/jss.v077.i02
  start: '1'
  end: '20'
- type: article
  title: Learning Bayesian Networks with the bnlearn R Package
  authors:
  - family-names: Scutari
    given-names: Marco
    email: marco.scutari@stat.unipd.it
  journal: Journal of Statistical Software
  year: '2010'
  volume: '35'
  issue: '3'
  doi: 10.18637/jss.v035.i03
  start: '1'
  end: '22'