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catnet

R package catnet: Categorical Bayesian Network Inference. A package that handles discrete Bayesian network models and provides inference using the frequentist approach

Keywords for this software

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  • Bayesian networks
  • R
  • R package
  • structure learning
  • Additive Bayesian Networks
  • GLM
  • belief propagation
  • graphical models
  • arXiv_stat.ML
  • scoring algorithm
  • visualization
  • jstatsoft.org
  • statistical computing
  • categorical data
  • Bayesian inference
  • penalized maximum likelihood
  • network scores
  • climate networks
  • Bayesian learning
  • graph theory
  • greedy search
  • arXiv_cs.LG
  • missing completely at random
  • model selection
  • gene networks
  • exact search
  • arXiv_publication
  • Probabilistic Reasoning
  • Machine Learning
  • Bayesian Networks

  • URL: cran.r-project.org/web...
  • Code
  • InternetArchive
  • Manual: cran.r-project.org/web...
  • Authors: Nikolay Balov, Peter Salzman
  • Dependencies: R

  • Add information on this software.


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References in zbMATH (referenced in 5 articles )

Showing results 1 to 5 of 5.
y Sorted by year (citations)

  1. Han Yu; Janhavi Moharil; Rachael Hageman Blair: BayesNetBP: An R Package for Probabilistic Reasoning in Bayesian Networks (2020) not zbMATH
  2. Gilles Kratzer, Fraser Iain Lewis, Arianna Comin, Marta Pittavino, Reinhard Furrer: Additive Bayesian Network Modelling with the R Package abn (2019) arXiv
  3. Scutari, Marco; Graafland, Catharina Elisabeth; Gutiérrez, José Manuel: Who learns better Bayesian network structures: accuracy and speed of structure learning algorithms (2019)
  4. Scutari, Marco; Denis, Jean-Baptiste: Bayesian networks. With examples in R (2015)
  5. Balov, Nikolay: Consistent model selection of discrete Bayesian networks from incomplete data (2013)

  • Article statistics & filter:

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  • MSC classification / top
    • Top MSC classes
      • 62 Statistics
      • 65 Numerical analysis
      • 68 Computer science

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