Package: bnlearn
Type: Package
Title: Bayesian Network Structure Learning, Parameter Learning and
        Inference
Version: 4.4.1
Date: 2019-03-05
Depends: R (>= 2.14.0), methods
Suggests: parallel, graph, Rgraphviz, lattice, gRain, ROCR, Rmpfr, gmp
Author: Marco Scutari [aut, cre], Robert Ness [ctb]
Maintainer: Marco Scutari <marco.scutari@gmail.com>
Description: Bayesian network structure learning, parameter learning and
  inference.
  This package implements constraint-based (PC, GS, IAMB, Inter-IAMB, Fast-IAMB,
  MMPC, Hiton-PC), pairwise (ARACNE and Chow-Liu), score-based (Hill-Climbing
  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 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 and
  cross-validation. Development snapshots with the latest bugfixes are
  available from <http://www.bnlearn.com>.
URL: http://www.bnlearn.com/
License: GPL (>= 2)
LazyData: yes
NeedsCompilation: yes
Packaged: 2019-03-05 15:57:40 UTC; scutari
Repository: CRAN
Date/Publication: 2019-03-05 22:00:03 UTC
Built: R 3.5.1; x86_64-w64-mingw32; 2019-07-19 22:03:13 UTC; windows
Archs: x64
