Bayesian network structure learning, parameter learning and
inference.
This package implements constraintbased (GS, IAMB, InterIAMB, FastIAMB,
MMPC, HitonPC), pairwise (ARACNE and ChowLiu), scorebased (HillClimbing
and Tabu Search) and hybrid (MMHC and RSMAX2) structure learning algorithms
for discrete, Gaussian and conditional Gaussian networks, along with many
score functions and conditional independence tests.
The Naive Bayes and the TreeAugmented 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 and
crossvalidation. Development snapshots with the latest bugfixes are
available from
Package details 


Author  Marco Scutari [aut, cre], Robert Ness [ctb] 
Date of publication  20170703 13:35:15 UTC 
Maintainer  Marco Scutari <marco.scutari@gmail.com> 
License  GPL (>= 2) 
Version  4.2 
URL  http://www.bnlearn.com/ 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

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